ALBERT

Description: Rock permeability is an important parameter for the formation evaluation. In this paper, a new method with streaming current is proposed to determine the sample permeability based on the electrokinetic effects, and is proved by the experimental measurements. Corresponding to this method, we have designed an experimental setup and a test system, then performed the streaming current (potential) and electro-osmosis pressure experiments with 23 sandstone samples at 0.05 mol l –1 NaCl solution. The streaming current (potential) coefficient and electro-osmosis pressure coefficient are obtained, respectively, with the experimental data at low frequencies with AC lock-in technique. The electrokinetic permeabilities are further calculated with these coefficients. The results are consistent well with the gas permeability measured with Darcy's law, which verifies the current method for estimating rock permeability. Our measurements are also analysed and compared with previous measurements. The results indicate that our method can reflect the essence of electrokinetic effects better and simplify the electrokinetic measurements as well. In addition, we discuss the influences of experimental artefacts (core holder and confining pressure installation) on the electrokinetic data. The results show that the trough phenomenon, appeared in frequency curves of streaming current (potential) coefficients, is induced by the resonance of the core-holder/vibrator system. This is important for the design of electrokinetic setup and the analysis of low-frequency response of the electrokinetic coupling coefficients.

Description: Multiparameter full waveform inversion (FWI) applied to an elastic orthorhombic model description of the subsurface requires in theory a nine-parameter representation of each pixel of the model. Even with optimal acquisition on the Earth surface that includes large offsets, full azimuth, and multicomponent sensors, the potential for trade-off between the elastic orthorhombic parameters are large. The first step to understanding such trade-off is analysing the scattering potential of each parameter, and specifically, its scattering radiation patterns. We investigate such radiation patterns for diffraction and for scattering from a horizontal reflector considering a background isotropic model. The radiation patterns show considerable potential for trade-off between the parameters and the potentially limited resolution in their recovery. The radiation patterns of C 11 , C 22 , and C 33 are well separated so that we expect to recover these parameters with limited trade-offs. However, the resolution of their recovery represented by recovered range of model wavenumbers varies between these parameters. We can only invert for the short wavelength components (reflection) of C 33 while we can mainly invert for the long wavelength components (transmission) of the elastic coefficients C 11 and C 22 if we have large enough offsets. The elastic coefficients C 13 , C 23 , and C 12 suffer from strong trade-offs with C 55 , C 44 , and C 66 , respectively. The trade-offs between C 13 and C 55 , as well as C 23 and C 44 , can be partially mitigated if we acquire P – SV and SV – SV waves. However, to reduce the trade-offs between C 12 and C 66 , we require credible SH – SH waves. The analytical radiation patterns of the elastic constants are supported by numerical gradients of these parameters.

Description: Typically, seismic data are sparsely and irregularly sampled due to limitations in the survey environment and these cause problems for key seismic processing steps such as surface-related multiple elimination or wave-equation-based migration. Various interpolation techniques have been developed to alleviate the problems caused by sparse and irregular sampling. Among many interpolation techniques, matching pursuit interpolation is a robust tool to interpolate the regularly sampled data with large receiver separation such as crossline data in marine seismic acquisition when both pressure and particle velocity data are used. Multicomponent matching pursuit methods generally used the sinusoidal basis function, which have shown to be effective for interpolating multicomponent marine seismic data in the crossline direction. In this paper, we report the use of wavelet basis functions which further enhances the performance of matching pursuit methods for de-aliasing than sinusoidal basis functions. We also found that the range of the peak wavenumber of the wavelet is critical to the stability of the interpolation results and the de-aliasing performance and that the range should be determined based on Nyquist criteria. In addition, we reduced the computational cost by adopting the inner product of the wavelet and the input data to find the parameters of the wavelet basis function instead of using L-2 norm minimization. Using synthetic data, we illustrate that for aliased data, wavelet-based matching pursuit interpolation yields more stable results than sinusoidal function-based one when we use not only pressure data only but also both pressure and particle velocity together.

Description: Assigning cancer patients to the most effective treatments requires an understanding of the molecular basis of their disease. While DNA-based molecular profiling approaches have flourished over the past several years to transform our understanding of driver pathways across a broad range of tumors, a systematic characterization of key driver pathways based on RNA data has not been undertaken. Here we introduce a new approach for predicting the status of driver cancer pathways based on signature functions derived from RNA sequencing data. To identify the driver cancer pathways of interest, we mined DNA variant data from TCGA and nominated driver alterations in seven major cancer pathways in breast, ovarian and colon cancer tumors. The activation status of these driver pathways were then characterized using RNA sequencing data by constructing classification signature functions in training datasets and then testing the accuracy of the signatures in test datasets. The signature functions differentiate well tumors with nominated pathway activation from tumors with no signs of activation: average AUC equals to 0.83. Our results confirm that driver genomic alterations are distinctively displayed at the transcriptional level and that the transcriptional signatures can generally provide an alternative to DNA sequencing methods in detecting specific driver pathways.

Description: Modeling the properties and functions of DNA sequences is an important, but challenging task in the broad field of genomics. This task is particularly difficult for non-coding DNA, the vast majority of which is still poorly understood in terms of function. A powerful predictive model for the function of non-coding DNA can have enormous benefit for both basic science and translational research because over 98% of the human genome is non-coding and 93% of disease-associated variants lie in these regions. To address this need, we propose DanQ, a novel hybrid convolutional and bi-directional long short-term memory recurrent neural network framework for predicting non-coding function de novo from sequence. In the DanQ model, the convolution layer captures regulatory motifs, while the recurrent layer captures long-term dependencies between the motifs in order to learn a regulatory ‘grammar’ to improve predictions. DanQ improves considerably upon other models across several metrics. For some regulatory markers, DanQ can achieve over a 50% relative improvement in the area under the precision-recall curve metric compared to related models. We have made the source code available at the github repository http://github.com/uci-cbcl/DanQ .

Description: Molecular sequences in public databases are mostly annotated by the submitting authors without further validation. This procedure can generate erroneous taxonomic sequence labels. Mislabeled sequences are hard to identify, and they can induce downstream errors because new sequences are typically annotated using existing ones. Furthermore, taxonomic mislabelings in reference sequence databases can bias metagenetic studies which rely on the taxonomy. Despite significant efforts to improve the quality of taxonomic annotations, the curation rate is low because of the labor-intensive manual curation process. Here, we present SATIVA, a phylogeny-aware method to automatically identify taxonomically mislabeled sequences (‘mislabels’) using statistical models of evolution. We use the Evolutionary Placement Algorithm (EPA) to detect and score sequences whose taxonomic annotation is not supported by the underlying phylogenetic signal, and automatically propose a corrected taxonomic classification for those. Using simulated data, we show that our method attains high accuracy for identification (96.9% sensitivity/91.7% precision) as well as correction (94.9% sensitivity/89.9% precision) of mislabels. Furthermore, an analysis of four widely used microbial 16S reference databases (Greengenes, LTP, RDP and SILVA) indicates that they currently contain between 0.2% and 2.5% mislabels. Finally, we use SATIVA to perform an in-depth evaluation of alternative taxonomies for Cyanobacteria. SATIVA is freely available at https://github.com/amkozlov/sativa .

Description: DNA microarrays and RNAseq are complementary methods for studying RNA molecules. Current computational methods to determine alternative exon usage (AEU) using such data require impractical visual inspection and still yield high false-positive rates. Integrated Gene and Exon Model of Splicing (iGEMS) adapts a gene-level residuals model with a gene size adjusted false discovery rate and exon-level analysis to circumvent these limitations. iGEMS was applied to two new DNA microarray datasets, including the high coverage Human Transcriptome Arrays 2.0 and performance was validated using RT-qPCR. First, AEU was studied in adipocytes treated with ( n = 9) or without ( n = 8) the anti-diabetes drug, rosiglitazone. iGEMS identified 555 genes with AEU, and robust verification by RT-qPCR (~90%). Second, in a three-way human tissue comparison (muscle, adipose and blood, n = 41) iGEMS identified 4421 genes with at least one AEU event, with excellent RT-qPCR verification (95%, n = 22). Importantly, iGEMS identified a variety of AEU events, including 3'UTR extension, as well as exon inclusion/exclusion impacting on protein kinase and extracellular matrix domains. In conclusion, iGEMS is a robust method for identification of AEU while the variety of exon usage between human tissues is 5–10 times more prevalent than reported by the Genotype-Tissue Expression consortium using RNA sequencing.

Description: Deep sea pockmarks underlain by chimney-like or pipe structures that contain methane hydrate are abundant along the Norwegian continental margin. In such hydrate provinces the interaction between hydrate formation and fluid flow has significance for benthic ecosystems and possibly climate change. The Nyegga region, situated on the western Norwegian continental slope, is characterized by an extensive pockmark field known to accommodate substantial methane gas hydrate deposits. The aim of this study is to detect and delineate both the gas hydrate and free gas reservoirs at one of Nyegga's pockmarks. In 2012, a marine controlled-source electromagnetic (CSEM) survey was performed at a pockmark in this region, where high-resolution 3-D seismic data were previously collected in 2006. 2-D CSEM inversions were computed using the data acquired by ocean bottom electrical field receivers. Our results, derived from unconstrained and seismically constrained CSEM inversions, suggest the presence of two distinctive resistivity anomalies beneath the pockmark: a shallow vertical anomaly at the underlying pipe structure, likely due to gas hydrate accumulation, and a laterally extensive anomaly attributed to a free gas zone below the base of the gas hydrate stability zone. This work contributes to a robust characterization of gas hydrate deposits within subseafloor fluid flow pipe structures.

Description: One of the main applications of magnetic field measurements in boreholes is the detection of unexploded ordnance or buried utility structures like pipes or tiebacks. Even though the advantage of fully oriented magnetic vector measurements have long been recognized and could significantly reduce costs and risks, the tools used for those purposes typically measure only the total magnetic field, the vertical and horizontal components or gradients thereof. The Göttingen Bohrloch Magnetometer uses three fibre optic gyros to record its orientation and thus enables us to compute high-quality three-component magnetic vector data regardless of borehole orientation. The measurements described in this paper were run in the scientific borehole Cuxhaven Lüdingworth 1/1A, which was drilled as a part of the ‘Coastal Aquifer Test field’ project to study the dynamics of the saltwater/freshwater interface. As the drill string got stuck during drilling of the first borehole, a second hole was drilled in the immediate vicinity. The drill string lies at a depth between 80 and 114 m at a distance of only 2.5 m southeast of the borehole used for the measurements, making it an ideal target to demonstrate the benefits of vector magnetic surveys. Although the theories to calculate magnetic fields of objects with different shapes is well established and do not need to be tested, they almost exclusively include approximations of the geometry. It is not obvious whether these approximations are suited to describe real data, or whether additional effects or refinements have to be considered. We use both a simplified monopole model and a cylinder model to fit the data and are able to determine the position of the drill string within a statistical error of approximately 10 cm. Additionally, we show that the location of the drill string could not have been determined by measurements of the total field or its horizontal and vertical component alone and that those methods would require the drilling of additional boreholes to obtain an unambiguous result.

Description: The Cancer Genome Atlas (TCGA) research network has made public a large collection of clinical and molecular phenotypes of more than 10 000 tumor patients across 33 different tumor types. Using this cohort, TCGA has published over 20 marker papers detailing the genomic and epigenomic alterations associated with these tumor types. Although many important discoveries have been made by TCGA's research network, opportunities still exist to implement novel methods, thereby elucidating new biological pathways and diagnostic markers. However, mining the TCGA data presents several bioinformatics challenges, such as data retrieval and integration with clinical data and other molecular data types (e.g. RNA and DNA methylation). We developed an R/Bioconductor package called TCGAbiolinks to address these challenges and offer bioinformatics solutions by using a guided workflow to allow users to query, download and perform integrative analyses of TCGA data. We combined methods from computer science and statistics into the pipeline and incorporated methodologies developed in previous TCGA marker studies and in our own group. Using four different TCGA tumor types (Kidney, Brain, Breast and Colon) as examples, we provide case studies to illustrate examples of reproducibility, integrative analysis and utilization of different Bioconductor packages to advance and accelerate novel discoveries.

Description: Single cell RNA-seq experiments provide valuable insight into cellular heterogeneity but suffer from low coverage, 3' bias and technical noise. These unique properties of single cell RNA-seq data make study of alternative splicing difficult, and thus most single cell studies have restricted analysis of transcriptome variation to the gene level. To address these limitations, we developed SingleSplice, which uses a statistical model to detect genes whose isoform usage shows biological variation significantly exceeding technical noise in a population of single cells. Importantly, SingleSplice is tailored to the unique demands of single cell analysis, detecting isoform usage differences without attempting to infer expression levels for full-length transcripts. Using data from spike-in transcripts, we found that our approach detects variation in isoform usage among single cells with high sensitivity and specificity. We also applied SingleSplice to data from mouse embryonic stem cells and discovered a set of genes that show significant biological variation in isoform usage across the set of cells. A subset of these isoform differences are linked to cell cycle stage, suggesting a novel connection between alternative splicing and the cell cycle.

Description: The recent super-exponential growth in the amount of sequencing data generated worldwide has put techniques for compressed storage into the focus. Most available solutions, however, are strictly tied to specific bioinformatics formats, sometimes inheriting from them suboptimal design choices; this hinders flexible and effective data sharing. Here, we present CARGO (Compressed ARchiving for GenOmics), a high-level framework to automatically generate software systems optimized for the compressed storage of arbitrary types of large genomic data collections. Straightforward applications of our approach to FASTQ and SAM archives require a few lines of code, produce solutions that match and sometimes outperform specialized format-tailored compressors and scale well to multi-TB datasets. All CARGO software components can be freely downloaded for academic and non-commercial use from http://bio-cargo.sourceforge.net .

Description: Phasing of single nucleotide (SNV), and structural variations into chromosome-wide haplotypes in humans has been challenging, and required either trio sequencing or restricting phasing to population-based haplotypes. Selvaraj et al . demonstrated single individual SNV phasing is possible with proximity ligated (HiC) sequencing. Here, we demonstrate HiC can phase structural variants into phased scaffolds of SNVs. Since HiC data is noisy, and SV calling is challenging, we applied a range of supervised classification techniques, including Support Vector Machines and Random Forest, to phase deletions. Our approach was demonstrated on deletion calls and phasings on the NA12878 human genome. We used three NA12878 chromosomes and simulated chromosomes to train model parameters. The remaining NA12878 chromosomes withheld from training were used to evaluate phasing accuracy. Random Forest had the highest accuracy and correctly phased 86% of the deletions with allele-specific read evidence. Allele-specific read evidence was found for 76% of the deletions. HiC provides significant read evidence for accurately phasing 33% of the deletions. Also, eight of eight top ranked deletions phased by only HiC were validated using long range polymerase chain reaction and Sanger. Thus, deletions from a single individual can be accurately phased using a combination of shotgun and proximity ligation sequencing. InPhaDel software is available at: http://l337x911.github.io/inphadel/.

Description: Many genomes display high levels of heterozygosity (i.e. presence of different alleles at the same loci in homologous chromosomes), being those of hybrid organisms an extreme such case. The assembly of highly heterozygous genomes from short sequencing reads is a challenging task because it is difficult to accurately recover the different haplotypes. When confronted with highly heterozygous genomes, the standard assembly process tends to collapse homozygous regions and reports heterozygous regions in alternative contigs. The boundaries between homozygous and heterozygous regions result in multiple assembly paths that are hard to resolve, which leads to highly fragmented assemblies with a total size larger than expected. This, in turn, causes numerous problems in downstream analyses such as fragmented gene models, wrong gene copy number, or broken synteny. To circumvent these caveats we have developed a pipeline that specifically deals with the assembly of heterozygous genomes by introducing a step to recognise and selectively remove alternative heterozygous contigs. We tested our pipeline on simulated and naturally-occurring heterozygous genomes and compared its accuracy to other existing tools. Our method is freely available at https://github.com/Gabaldonlab/redundans .

Description: Although seismic attenuation measurements have great potential to enhance our knowledge of physical conditions and rock properties, their application is limited because robust methods for improving both the resolution and accuracy of attenuation estimates have not yet been established. We propose attenuation estimation methods for zero-offset vertical seismic profile (VSP) data by combining seismic interferometry (SI) and the modified median frequency shift (MMFS) method developed for attenuation estimation using sonic waveform data. The configuration of zero-offset VSP data is redatumed to that of the sonic logging measurement by adopting two types of SI: deconvolution interferometry and crosscorrelation interferometry (CCI). Then, we can apply the MMFS method to the redatumed VSP data. Although the amplitude information estimated from CCI is biased, we propose a correction method for this bias to correctly estimate attenuation. First, to investigate the performance both in resolution and accuracy, we apply different trace separations to synthetic data with random noise at different signal-to-noise ratio levels. Second, we estimate the influence of residual reflection events after wavefield separation on attenuation estimation. The proposed methods provide more stable attenuation estimates in comparison with the spectral ratio method because the mean-median procedure suppresses random events and characteristic features caused by residual reflection events in spectral domain. Our numerical experiments also imply that the proposed methods can estimate scattering attenuation values even if frequency components are not changed between the two receiver depths. Finally, by preliminarily applying the proposed methods to field VSP data, we demonstrate the advantages of the proposed method in the resolution and stability of attenuation estimates and these observations correlate with those of numerical tests.

Description: Capacitively Coupled Resistivity (CCR) is conventionally used to emulate DC resistivity measurements and may provide important information about the ice content of material in periglacial areas. The application of CCR theoretically enables the determination of both electrical parameters, that is, the resistivity and the electrical permittivity, by analysing magnitude and phase shift spectra. The electrical permittivity may dominate the impedance, especially in periglacial areas or regions of hydrogeological interest. However, previous theoretical work suggested that the phase shift may strongly depend on electrode height above ground, implying that electrode height must be known with great accuracy to determine electrical permittivity. Here, we demonstrate with laboratory test measurements, theoretical modelling and by analysing the Jacobian matrix of the inversion that the sensitivity towards electrode height is drastically reduced if the electrical permittivity is frequency dependent in a way that is typical for ice. For the first time, we used a novel broad-band CCR device ‘Chameleon’ for a field test located in one of the ridge galleries beneath the crest of Mount Zugspitze. A permanently ice covered bottom of a tunnel was examined. For the inversion of the measured spectra, the frequency dependence of the electrical parameters was parametrized in three different ways: A Debye Model for pure ices, a Cole–Cole Model for pure ices and a dual Cole–Cole Model including interfacial water additionally. The frequency-dependent resistivity and permittivity spectra obtained from the inversion, including low- and high-frequency limits, agree reasonably well with laboratory and field measurements reported in the literature.

Description: We evaluate the applicability and the effectiveness of GPR attribute analysis for high-resolution glacier imaging and characterization, testing this approach on 4-D GPR multifrequency data collected in a small glacier in the Eastern Alps, by repeating the acquisition along the same profiles in four different periods of the year 2013. The main objectives are to image and characterize the glacier's inner structure and to quantitatively monitor the seasonal thawing of near-surface frozen materials (snow/firn). A multiattribute approach is used to characterize the subsurface through different attribute categories, including instantaneous and textural attributes considering not only amplitude-, phase- and frequency-related attributes, but also other more complex and integrated parameters. We combine information from more than one attribute into a single image with composite displays, using overlays or mixed displays. The results demonstrate that the developed GPR attribute analysis can provide significant improvements in the discrimination of GPR signals, and obtain enhanced and more constrained data interpretations.

Description: Migration velocity analysis aims at automatically updating the large-scale components of the velocity model, called macromodel. Extended Common Image Gathers are panels used to evaluate focusing after imaging and are constructed as a function of a spatial shift introduced in the imaging condition. We investigate how transmitted waves can also be used in migration velocity analysis: instead of back-propagating the residuals associated with reflected waves, we propose to back-propagate the full wavefield. The image function, equivalent to the migrated section for reflected data, does not exhibit localized events in space along horizons but is still sensitive to the choice of the background velocity model and can thus be coupled to the same objective function defined in the image domain. In order to enhance the benefits of direct waves, we consider a cross-well configuration. Direct waves provide a large illumination between two vertical wells. Associated Common Image Gathers present different characteristics than the ones associated with reflected waves in surface acquisition. In particular, energy is spread over up to the maximum penetration depth. We invert cross-well seismic data along two lines. In the first case, the input data contain the full wavefield dominated by transmitted waves. It demonstrates the possibility to handle transmitted waves to determine the velocity model. It appears that the misfit in the data domain is largely reduced after inversion. In the second case, we use the same algorithm, but with reflected observed data only, as in a classical approach. Most of velocity updates are localized around the reflectivity, leading to an incorrect final model. This demonstrates the benefit of transmitted waves for migration velocity analysis in a cross-well configuration.

Description: An integrated approach to interpret Self-Potential (SP) anomalies based on spectral analysis and tomographic methods is presented. The Maximum Entropy Method (MEM) is used for providing accurate estimates of the depth of the anomaly source. The 2-D tomographic inversion technique, based on the underground charge occurrence probability (COP) function, is, then, used to fully characterize the anomalous body, as the MEM is not helpful in delineating the shape of the anomaly source. The proposed integrated approach is applied for the inversion of synthetic SP data generated by geometrically simple anomalous bodies, such as cylinders and inclined sheets. This numerical study has allowed the determination of mathematical relationships between zero lines of the COP distributions, the polarization angles and the positions along the profile of the causative sources, which have been of great help for interpreting the related SP anomalies. Finally, the analysis of field examples shows the high potential applicability of the proposed integrated approach for SP data inversion.

Description: Volcanic and tectonic events are the main processes involved in the generation of the oceanic crust and responsible for the seismicity associated with seafloor spreading. To monitor this activity, usually not or poorly detected by land-based seismological stations, we deployed from February 2012 to February 2013 a network of autonomous hydrophones to compare the behaviour of the ultraslow-spreading Southwest Indian ridge (SWIR) with that of the intermediate-spreading Southeast Indian ridge (SEIR). The rate of seismicity is similar for both ridges, suggesting that there is no systematic relationship between seismicity and spreading rates. The along-axis distribution of the seismic events, however, does differ, reflecting the rate dependence of accretion modes. Earthquakes are sparse and regularly spaced and scattered along the SWIR, reflecting prevailing tectonic processes. By contrast, along the SEIR, events are irregularly distributed and focus at ridge-segment ends and transforms faults, reflecting the ridge segmentation; only two swarms occurred at a segment centre and are probably caused by a magmatic event. This seismicity distribution thus looks controlled by segment-scale crustal heterogeneities along the SEIR and by regional-scale contrasting accretion processes along the SWIR, probably driven by different lithospheric and asthenospheric dynamics on either side of the Melville fracture zone. The comparison of hydroacoustic and teleseismic catalogues shows that, along these spreading ridges, the background seismicity observed in 1 yr by a hydroacoustic network is representative of the seismicity observed over two decades by land-based networks.

Description: Geothermal well GRT-1 (Rittershoffen, Alsace) was drilled in 2012. Its open-hole section (extending down to a depth of 2.6 km) penetrated fractured sandstones and granite. In 2013, the well was subjected to Thermal, Chemical and Hydraulic (TCH) stimulation, which improved the injectivity index fivefold. The goal of the study was to assess the impact of the stimulation by comparing pre- and post-stimulation well-logging (acoustic and temperature [ T ] logs) and mud-logging data. This comparison revealed modifications of almost all the natural fractures. However, not all of these fractures are associated with permeability enhancement, and the post-stimulation T logs are important for characterizing this enhancement. Chemical alteration due to mechanical erosion at the tops and bottoms of the fractures was observed in the sandstones. These zones display indications of very small new permeability after the TCH stimulation. Because a major fault zone caved extensively where it crosses the borehole, it was not imaged in the acoustic logs. However, this originally permeable zone was enhanced as demonstrated by the T logs. Based on the natural injectivity of this fault zone, hydraulic erosion and thermal microcracking of its internal quartz veins are associated with this permeability enhancement. Although local changes in the borehole wall observed in the acoustic images cannot be directly linked to the improved injectivity index, the comparison of the acoustic image logs allows for identification of fracture zones impacted by the TCH stimulation.

Description: We investigate the spatial coherence of underwater ambient noise using a yearlong time-series measured off Ascension Island. Qualitative agreement with observed cross-correlations is achieved using a simple range-dependent model, constrained by earlier, active tomographic studies in the area. In particular, the model correctly predicts the existence of two weakly dispersive normal modes in the microseism frequency range, with the group speed of one of the normal modes being smaller than the sound speed in water. The agreement justifies our interpretation of the peaks of the measured cross-correlation function of ambient noise as modal arrivals, with dispersion that is sensitive to crustal velocity structure. Our observations are consistent with Scholte to Moho head wave coupled propagation, with double mode conversion occurring due to the bathymetric variations between receivers. We thus demonstrate the feasibility of interrogating crustal properties using noise interferometry of moored hydrophone data at ranges in excess of 120 km.

Description: Recent tectonic reconstructions of the South Atlantic have partitioned the ocean basin into several segments based upon one or more proposed intraplate South American deformation zones. In several of these reconstructions, opening of the southern segment(s) by seafloor spreading prior to Aptian-Albian time is accompanied by contemporaneous strike-slip motion along an intraplate boundary extending southeastward from the Andean Cochabamba—Santa Cruz bend to the Rio Grande Fracture Zone (RGFZ). We have examined new magnetic data over the Pelotas, Santos and Campos Basins, offshore Argentina and Brazil, acquired by ION-GXT in tandem with long-offset, long record seismic reflection data, and identified seafloor spreading anomalies M4, M3, M2 and M0 (~131, ~129, ~128 and ~125 Ma). Integrating these results with our earlier work, we have been able to correlate magnetochrons M4, M3, M2 and M0 north and south of the RGFZ on the South American margin, and north and south of the Walvis Ridge on the African side. Our results are therefore inconsistent with diachronous opening models that involve substantial continental strike-slip motion north of RGFZ during M4 to M0 time. Although the ocean basin may have opened from south to north, our results indicate that seafloor spreading began north of the RGFZ earlier than previously proposed.

Description: Understanding telomere length maintenance mechanisms is central in cancer biology as their dysregulation is one of the hallmarks for immortalization of cancer cells. Important for this well-balanced control is the transcriptional regulation of the telomerase genes. We integrated Mixed Integer Linear Programming models into a comparative machine learning based approach to identify regulatory interactions that best explain the discrepancy of telomerase transcript levels in yeast mutants with deleted regulators showing aberrant telomere length, when compared to mutants with normal telomere length. We uncover novel regulators of telomerase expression, several of which affect histone levels or modifications. In particular, our results point to the transcription factors Sum1, Hst1 and Srb2 as being important for the regulation of EST1 transcription, and we validated the effect of Sum1 experimentally. We compiled our machine learning method leading to a user friendly package for R which can straightforwardly be applied to similar problems integrating gene regulator binding information and expression profiles of samples of e.g. different phenotypes, diseases or treatments.

Description: The ability to integrate ‘omics’ (i.e. transcriptomics and proteomics) is becoming increasingly important to the understanding of regulatory mechanisms. There are currently no tools available to identify differentially expressed genes (DEGs) across different ‘omics’ data types or multi-dimensional data including time courses. We present fCI (f-divergence Cut-out Index), a model capable of simultaneously identifying DEGs from continuous and discrete transcriptomic, proteomic and integrated proteogenomic data. We show that fCI can be used across multiple diverse sets of data and can unambiguously find genes that show functional modulation, developmental changes or misregulation. Applying fCI to several proteogenomics datasets, we identified a number of important genes that showed distinctive regulation patterns. The package fCI is available at R Bioconductor and http://software.steenlab.org/fCI/ .

Description: Next generation sequencing of cellular RNA is making it possible to characterize genes and alternative splicing in unprecedented detail. However, designing bioinformatics tools to accurately capture splicing variation has proven difficult. Current programs can find major isoforms of a gene but miss lower abundance variants, or are sensitive but imprecise. CLASS2 is a novel open source tool for accurate genome-guided transcriptome assembly from RNA-seq reads based on the model of splice graph. An extension of our program CLASS, CLASS2 jointly optimizes read patterns and the number of supporting reads to score and prioritize transcripts, implemented in a novel, scalable and efficient dynamic programming algorithm. When compared against reference programs, CLASS2 had the best overall accuracy and could detect up to twice as many splicing events with precision similar to the best reference program. Notably, it was the only tool to produce consistently reliable transcript models for a wide range of applications and sequencing strategies, including ribosomal RNA-depleted samples. Lightweight and multi-threaded, CLASS2 requires 〈3GB RAM and can analyze a 350 million read set within hours, and can be widely applied to transcriptomics studies ranging from clinical RNA sequencing, to alternative splicing analyses, and to the annotation of new genomes.

Description: Allele-specific copy number analysis (ASCN) from next generation sequencing (NGS) data can greatly extend the utility of NGS beyond the identification of mutations to precisely annotate the genome for the detection of homozygous/heterozygous deletions, copy-neutral loss-of-heterozygosity (LOH), allele-specific gains/amplifications. In addition, as targeted gene panels are increasingly used in clinical sequencing studies for the detection of ‘actionable’ mutations and copy number alterations to guide treatment decisions, accurate, tumor purity-, ploidy- and clonal heterogeneity-adjusted integer copy number calls are greatly needed to more reliably interpret NGS-based cancer gene copy number data in the context of clinical sequencing. We developed FACETS, an ASCN tool and open-source software with a broad application to whole genome, whole-exome, as well as targeted panel sequencing platforms. It is a fully integrated stand-alone pipeline that includes sequencing BAM file post-processing, joint segmentation of total- and allele-specific read counts, and integer copy number calls corrected for tumor purity, ploidy and clonal heterogeneity, with comprehensive output and integrated visualization. We demonstrate the application of FACETS using The Cancer Genome Atlas (TCGA) whole-exome sequencing of lung adenocarcinoma samples. We also demonstrate its application to a clinical sequencing platform based on a targeted gene panel.

Description: We present SWAN, a statistical framework for robust detection of genomic structural variants in next-generation sequencing data and an analysis of mid-range size insertion and deletions (〈10 Kb) for whole genome analysis and DNA mixtures. To identify these mid-range size events, SWAN collectively uses information from read-pair, read-depth and one end mapped reads through statistical likelihoods based on Poisson field models. SWAN also uses soft-clip/split read remapping to supplement the likelihood analysis and determine variant boundaries. The accuracy of SWAN is demonstrated by in silico spike-ins and by identification of known variants in the NA12878 genome. We used SWAN to identify a series of novel set of mid-range insertion/deletion detection that were confirmed by targeted deep re-sequencing. An R package implementation of SWAN is open source and freely available.

Description: High-throughput screening (HTS) is an indispensable tool for drug (target) discovery that currently lacks user-friendly software tools for the robust identification of putative hits from HTS experiments and for the interpretation of these findings in the context of systems biology. We developed HiTSeekR as a one-stop solution for chemical compound screens, siRNA knock-down and CRISPR/Cas9 knock-out screens, as well as microRNA inhibitor and -mimics screens. We chose three use cases that demonstrate the potential of HiTSeekR to fully exploit HTS screening data in quite heterogeneous contexts to generate novel hypotheses for follow-up experiments: (i) a genome-wide RNAi screen to uncover modulators of TNFα, (ii) a combined siRNA and miRNA mimics screen on vorinostat resistance and (iii) a small compound screen on KRAS synthetic lethality. HiTSeekR is publicly available at http://hitseekr.compbio.sdu.dk . It is the first approach to close the gap between raw data processing, network enrichment and wet lab target generation for various HTS screen types.

Description: Determining thin layer thickness is very important for reservoir characterization and CO 2 quantification. Given its high time–frequency resolution and robustness, the complex spectral decomposition method was applied on time-lapse 3-D seismic data from the Ketzin pilot site for CO 2 storage to evaluate the frequency-dependent characteristics of thin layers at the injection level. Higher temporal resolution and more stratigraphic details are seen in the all-frequency and monochromatic reflectivity amplitude sections obtained by complex spectral decomposition compared to the stacked sections. The mapped geologic discontinuities within the reservoir are consistent with the preferred orientation of CO 2 propagation. Tuning frequency mapping shows the thicknesses of the reservoir sandstone and gaseous CO 2 is consistent with the measured thickness of the sandstone unit from well logging. An attempt to discriminate between pressure effects and CO 2 saturation using the extracted tuning frequency indicates that CO 2 saturation is the main contributor to the amplitude anomaly at the Ketzin site. On the basis of determined thickness of gaseous CO 2 in the reservoir, quantitative analysis of the amount of CO 2 was performed and shows a discrepancy between the injected and calculated CO 2 mass. This may be explained by several uncertainties, like structural reservoir heterogeneity, a limited understanding of the complex subsurface conditions, error of determined tuning frequency, the presence of ambient noise and ongoing CO 2 dissolution.

Description: Comprehensive analytical solutions to 3-D axisymmetric problems for static response of multilayered thermoelastic media subjected to surface loads and containing sources are presented in this study. The solution strategy employs Laplace and Hankel transforms to the field variables. The problem is formulated in cylindrical coordinate system and in this coordinate system vector surface harmonics and generalized propagator matrix are introduced to find the solution for the problem for the behaviour of thermoelastic multilayered media subject to surface loads and containing heat sources. A high-order adaptive Gaussian quadrature method with continued fraction expansions is employed to approximate the integral solutions expressed in terms of semi-infinite Hankel-type integrals. It is the first time to apply the proposed solution method to investigate the behaviour of repository for heat-emitting high-level nuclear waste (HLW) in a geological formation where the HLW can be regarded as a decaying with time point heat source.

Description: We present a series of processes for understanding and analysing controlled-source electromagnetic (CSEM) responses for a conductive and permeable earth. To realize the CSEM response, a new 3-D CSEM forward modelling algorithm based on an edge finite element method for both electrically conductive and magnetically permeable heterogeneities is developed. The algorithm shows highly accurate results in validation tests against a semi-analytic solution for stratified earth and an integral form of the scattered field. We describe the vector behaviour of an anomalous magnetic field originating from a conductive and permeable anomaly when the loop sources are deployed over a conductive half-space. The CSEM response of the conductive and permeable anomaly is classified into three effects originating from: conductivity perturbations, permeability perturbations and the coupling of these two effects. The separated individual results and the corresponding integral equation form of the anomalous field help to better understand the physical behaviour. We confirm the characteristic features of the CSEM response from the conductive and permeable anomaly, for example, (1) the general dominance of the induction effect in the out-of-phase response accompanied by a non-negligible magnetization effect from the magnetic anomaly in a conductive half-space and (2) the dominance of near frequency-independent magnetization effects in the in-phase response at relatively low frequencies and change in ruling part of the in-phase response into the induction effect as the frequency increases. We also demonstrate the effect of coupling mode and show that its maximum contribution is limited to a few per cent level of other two modes, induction and magnetization mode, even when the heterogeneity of our model is strong. In our synthetic survey, using examples of land-based profiling surveys of low induction number and intermediate regime, we find that the effect of magnetization can be used as an indicator of the existence of magnetic material. One important point to note from this study is the importance of accurate cancelling-out or estimation of free-space responses, which can mask the magnetic responses to imaging the varying magnetic property.

Description: Disease-gene identification is a challenging process that has multiple applications within functional genomics and personalized medicine. Typically, this process involves both finding genes known to be associated with the disease (through literature search) and carrying out preliminary experiments or screens (e.g. linkage or association studies, copy number analyses, expression profiling) to determine a set of promising candidates for experimental validation. This requires extensive time and monetary resources. We describe Beegle , an online search and discovery engine that attempts to simplify this process by automating the typical approaches. It starts by mining the literature to quickly extract a set of genes known to be linked with a given query, then it integrates the learning methodology of Endeavour (a gene prioritization tool) to train a genomic model and rank a set of candidate genes to generate novel hypotheses. In a realistic evaluation setup, Beegle has an average recall of 84% in the top 100 returned genes as a search engine, which improves the discovery engine by 12.6% in the top 5% prioritized genes. Beegle is publicly available at http://beegle.esat.kuleuven.be/ .

Description: Alternative splicing is an important mechanism in eukaryotes that expands the transcriptome and proteome significantly. It plays an important role in a number of biological processes. Understanding its regulation is hence an important challenge. Recently, increasing evidence has been collected that supports an involvement of intragenic DNA methylation in the regulation of alternative splicing. The exact mechanisms of regulation, however, are largely unknown, and speculated to be complex: different methylation profiles might exist, each of which could be associated with a different regulation mechanism. We present a computational technique that is able to determine such stable methylation patterns and allows to correlate these patterns with inclusion propensity of exons. Pattern detection is based on dynamic time warping (DTW) of methylation profiles, a sophisticated similarity measure for signals that can be non-trivially transformed. We design a flexible self-organizing map approach to pattern grouping. Exemplary application on available data sets indicates that stable patterns which correlate non-trivially with exon inclusion do indeed exist. To improve the reliability of these predictions, further studies on larger data sets will be required. We have thus taken great care that our software runs efficiently on modern hardware, so that it can support future studies on large-scale data sets.

Description: Extraction of fluids from subsurface reservoirs induces changes in pore pressure, leading not only to geomechanical changes, but also perturbations in seismic velocities and hence observable seismic attributes. Time-lapse seismic analysis can be used to estimate changes in subsurface hydromechanical properties and thus act as a monitoring tool for geological reservoirs. The ability to observe and quantify changes in fluid, stress and strain using seismic techniques has important implications for monitoring risk not only for petroleum applications but also for geological storage of CO 2 and nuclear waste scenarios. In this paper, we integrate hydromechanical simulation results with rock physics models and full-waveform seismic modelling to assess time-lapse seismic attribute resolution for dynamic reservoir characterization and hydromechanical model calibration. The time-lapse seismic simulations use a dynamic elastic reservoir model based on a North Sea deep reservoir undergoing large pressure changes. The time-lapse seismic traveltime shifts and time strains calculated from the modelled and processed synthetic data sets (i.e. pre-stack and post-stack data) are in a reasonable agreement with the true earth models, indicating the feasibility of using 1-D strain rock physics transform and time-lapse seismic processing methodology. Estimated vertical traveltime shifts for the overburden and the majority of the reservoir are within ±1 ms of the true earth model values, indicating that the time-lapse technique is sufficiently accurate for predicting overburden velocity changes and hence geomechanical effects. Characterization of deeper structure below the overburden becomes less accurate, where more advanced time-lapse seismic processing and migration is needed to handle the complex geometry and strong lateral induced velocity changes. Nevertheless, both migrated full-offset pre-stack and near-offset post-stack data image the general features of both the overburden and reservoir units. More importantly, the results from this study indicate that integrated seismic and hydromechanical modelling can help constrain time-lapse uncertainty and hence reduce risk due to fluid extraction and injection.

Description: A new plate motions model for the northwest Africa–North America Plate pair during the Oligocene and early Miocene is presented. The model is accompanied by a high-resolution isochron map for the central Atlantic region, resulting from a re-examination of 423 ship tracks from the NGDC data base for the area between the 15°20' FZ and the Azores triple junction. A new digital model of fracture zones for this region and a set of 309 magnetic profiles crossing the Oligocene to recent oceanic crust within the study area allowed to determine accurate finite reconstruction poles for the North America–northwest Africa conjugate plate pair between the early Miocene (Chron 6) and the early Oligocene (Chron 13). For times older than Chron 7 (~25 Ma), the finite reconstruction poles were calculated using a reliable data set coming exclusively from the region south of the Canary Islands FZ (~32°N), which allowed to test the rigidity of the northwest African oceanic lithosphere during the Oligocene–early Miocene phase of Atlas orogeny. A comparison of theoretical magnetic isochrons with observed magnetic lineations systematically shows that anomalously high spreading rates occurred in the area north of the Canary Islands FZ before Chron 7, thereby suggesting that the formation of the Atlas mountain, rather than being a localized intracontinental process, was logically linked to the central Atlantic spreading history. Thus, an independent Moroccan Plate could have existed during the Oligocene–early Miocene time interval, which included both the oceanic lithosphere north of the Canary Islands FZ and the northern Maghrebian areas of Morocco, Algeria and Tunisia. In this eventuality, the Atlas mountain belt should be reinterpreted as a giant flower structure associated with dextral transpression.

Description: Spectral induced polarization measurements are affected by temperature variations due to a variety of temperature-dependent parameters that control the complex electrical conductivity. Most important is the influence of the ion mobility, which increases with increasing temperature. It is responsible for the increase of the conductivity of the fluid in the pores with temperature and influences the electrical double layer on the mineral surface. This work is based on laboratory measurements of 13 sandstone samples from different sources with different geological and petrophysical characteristics. We measured the complex impedance in a frequency range from 0.01 to 100 Hz and a temperature range from 0 to 40 °C. The main observation is a decrease of the characteristic time (defined by the inverse of the frequency, at which the phase shift is maximum) with increasing temperature. The strength of this decrease differs from one sample to another. The temperature dependence of the phase shift magnitude cannot easily be generalized, as it depends on the particular sample. The experimental findings suggest that neglecting the influence of temperature on complex conductivity may lead to significant errors when estimating hydraulic conductivity from relaxation time. We also simulate the temperature dependence with a theoretical model of membrane polarization and review some of the model properties, with an emphasis on the temperature dependence of the parameters. The model reproduces several features characterizing the measured data, including the temperature dependence of the characteristic times. Computed tomography and microscope images of the pore structure of three samples also allow us to associate differences in the geometrical parameters used in the modelling with pore scale parameters of the actual samples.

Description: Knowledge about the pressure dependency of elastic and electrical properties is important for a variety of geophysical applications. We present a technique to invert for the stiff and compliant porosity from velocity measurements made as a function of differential pressure on saturated sandstones. A dual porosity concept is used for dry rock compressibility and a squirt model is employed for the pressure and frequency dependent elastic properties of the rocks when saturated. The total porosity obtained from inversion shows satisfactory agreement with experimental results. The electrical cementation factor was determined using the inverted porosity in combination with measured electrical conductivity. It was found that cementation factor increased exponentially with increasing differential pressure during isostatic loading. Elastic compressibility, electrical cementation factor and electrical conductivity of the saturated rocks correlate linearly with compliant porosity, and electrical cementation factor and electrical conductivity exhibit linear correlations with elastic compressibility of the saturated rocks under loading. The results show that the dual porosity concept is sufficient to explain the pressure dependency of elastic, electrical and joint elastic-electrical properties of saturated porous sandstones.

Description: A new plate motions model for the northwest Africa–North America Plate pair during the Oligocene and early Miocene is presented. The model is accompanied by a high-resolution isochron map for the central Atlantic region, resulting from a re-examination of 423 ship tracks from the NGDC data base for the area between the 15°20' FZ and the Azores triple junction. A new digital model of fracture zones for this region and a set of 309 magnetic profiles crossing the Oligocene to recent oceanic crust within the study area allowed to determine accurate finite reconstruction poles for the North America–northwest Africa conjugate plate pair between the early Miocene (Chron 6) and the early Oligocene (Chron 13). For times older than Chron 7 (~25 Ma), the finite reconstruction poles were calculated using a reliable data set coming exclusively from the region south of the Canary Islands FZ (~32°N), which allowed to test the rigidity of the northwest African oceanic lithosphere during the Oligocene–early Miocene phase of Atlas orogeny. A comparison of theoretical magnetic isochrons with observed magnetic lineations systematically shows that anomalously high spreading rates occurred in the area north of the Canary Islands FZ before Chron 7, thereby suggesting that the formation of the Atlas mountain, rather than being a localized intracontinental process, was logically linked to the central Atlantic spreading history. Thus, an independent Moroccan Plate could have existed during the Oligocene–early Miocene time interval, which included both the oceanic lithosphere north of the Canary Islands FZ and the northern Maghrebian areas of Morocco, Algeria and Tunisia. In this eventuality, the Atlas mountain belt should be reinterpreted as a giant flower structure associated with dextral transpression.

Description: Tumors are characterized by properties of genetic instability, heterogeneity, and significant oligoclonality. Elucidating this intratumoral heterogeneity is challenging but important. In this study, we propose a framework, BubbleTree, to characterize the tumor clonality using next generation sequencing (NGS) data. BubbleTree simultaneously elucidates the complexity of a tumor biopsy, estimating cancerous cell purity, tumor ploidy, allele-specific copy number, and clonality and represents this in an intuitive graph. We further developed a three-step heuristic method to automate the interpretation of the BubbleTree graph, using a divide-and-conquer strategy. In this study, we demonstrated the performance of BubbleTree with comparisons to similar commonly used tools such as THetA2, ABSOLUTE, AbsCN-seq and ASCAT, using both simulated and patient-derived data. BubbleTree outperformed these tools, particularly in identifying tumor subclonal populations and polyploidy. We further demonstrated BubbleTree's utility in tracking clonality changes from patients’ primary to metastatic tumor and dating somatic single nucleotide and copy number variants along the tumor clonal evolution. Overall, the BubbleTree graph and corresponding model is a powerful approach to provide a comprehensive spectrum of the heterogeneous tumor karyotype in human tumors. BubbleTree is R-based and freely available to the research community ( https://www.bioconductor.org/packages/release/bioc/html/BubbleTree.html ).

Description: Maximizing vertical resolution is a key objective in seismic data processing. Early deconvolution and spectral balancing algorithms assumed that the seismic source wavelet was temporally invariant, or stationary. In practice, seismic scattering and attenuation give rise to non-stationary seismic source wavelets. To address this issue, most conventional time-varying deconvolution wavelet shaping and spectral modelling techniques using the stationary polynomial fitting assume the wavelet to be locally stationary within a small number of overlapping analysis windows while the fitting coefficients are invariant with all the frequencies. In this paper, we show an improvement obtained by modelling smoothly varying spectra of the seismic wavelet using non-stationary polynomial fitting in the time–frequency domain. We first decompose each seismic trace using a generalized S-transform that provides a good time–frequency distribution for the estimation of the time-varying wavelet spectra. We then model the slowly varying source wavelet spectrum at each time sample by a smooth low-order polynomial. Finally, we spectrally balance the modelled wavelet to flatten the seismic response, thereby increasing vertical resolution. We calibrate the algorithm on a simple synthetic and then apply it to a 3-D land survey acquired in western China, showing the value on both vertical slices through seismic amplitude and attribute time slices. Our new algorithm significantly improves the vertical resolution of the seismic signal, while not increasing the noise.

Description: Knowledge about the pressure dependency of elastic and electrical properties is important for a variety of geophysical applications. We present a technique to invert for the stiff and compliant porosity from velocity measurements made as a function of differential pressure on saturated sandstones. A dual porosity concept is used for dry rock compressibility and a squirt model is employed for the pressure and frequency dependent elastic properties of the rocks when saturated. The total porosity obtained from inversion shows satisfactory agreement with experimental results. The electrical cementation factor was determined using the inverted porosity in combination with measured electrical conductivity. It was found that cementation factor increased exponentially with increasing differential pressure during isostatic loading. Elastic compressibility, electrical cementation factor and electrical conductivity of the saturated rocks correlate linearly with compliant porosity, and electrical cementation factor and electrical conductivity exhibit linear correlations with elastic compressibility of the saturated rocks under loading. The results show that the dual porosity concept is sufficient to explain the pressure dependency of elastic, electrical and joint elastic-electrical properties of saturated porous sandstones.

Description: In order to perform gas exploration and determine the distribution pattern of gas in the Yanchang Oil Field in the eastern part of the North Shaanxi Slope, Ordos Basin, China, gravity and magnetic survey data were systemically collated, processed and interpreted in combination with the drilling data and recent seismic data. The genesis of gravity and magnetic anomalies and the relationship between the characteristics of the gravity and magnetic fields and known gas distribution were explored in order to predict the favourable exploration targets for gas. Gravity anomalies resulted both from the lateral variation in density of the basement rock and lateral lithologic transformation in the sedimentary cover. The regional magnetic anomalies were mainly caused by the basement metamorphic rocks and the residual magnetic anomalies may reflect the amount and general location of the volcanic materials in the overlying strata. The residual gravity and magnetic anomalies generated by high-density sandstone and high content of volcanics in the gas reservoir of the upper Paleozoic distorted and deformed the anomaly curves when they were stacked onto the primary background anomaly. The gas wells were generally found to be located in the anomaly gradient zones, or the distorted part of contour lines, and the flanks of high and low anomalies, or the transitional zones between anomaly highs and lows. The characteristics of gravity and magnetic fields provide significant information that can be used for guidance when exploring the distribution of gas. Based on these characteristics, five favourable areas for gas exploration were identified; these are quasi-equally spaced like a strip extending from the southeast to the northwest.

Description: Spectral induced polarization measurements are affected by temperature variations due to a variety of temperature-dependent parameters that control the complex electrical conductivity. Most important is the influence of the ion mobility, which increases with increasing temperature. It is responsible for the increase of the conductivity of the fluid in the pores with temperature and influences the electrical double layer on the mineral surface. This work is based on laboratory measurements of 13 sandstone samples from different sources with different geological and petrophysical characteristics. We measured the complex impedance in a frequency range from 0.01 to 100 Hz and a temperature range from 0 to 40 °C. The main observation is a decrease of the characteristic time (defined by the inverse of the frequency, at which the phase shift is maximum) with increasing temperature. The strength of this decrease differs from one sample to another. The temperature dependence of the phase shift magnitude cannot easily be generalized, as it depends on the particular sample. The experimental findings suggest that neglecting the influence of temperature on complex conductivity may lead to significant errors when estimating hydraulic conductivity from relaxation time. We also simulate the temperature dependence with a theoretical model of membrane polarization and review some of the model properties, with an emphasis on the temperature dependence of the parameters. The model reproduces several features characterizing the measured data, including the temperature dependence of the characteristic times. Computed tomography and microscope images of the pore structure of three samples also allow us to associate differences in the geometrical parameters used in the modelling with pore scale parameters of the actual samples.

Description: The streaming potential phenomenon is produced by the flow of an electrolyte in a porous medium and is used for geophysical prospecting. It is quantified through an electrokinetic (EK) coefficient. The dependence of the EK coefficient on the conductivity of the electrolyte is described by the Helmholtz–Smoluchowski (HS) equation. This equation provides successful forecasts of the EK coefficient in the standard range of concentration. However, experimental measurements show deviations to this equation at extreme low and extreme high salinities. The aim of this study is to model the EK coefficient using Lattice Boltzmann simulations in a 2-D capillary channel, with a view to understanding these deviations. The effect of the constitutive parameters of the HS equation such as the permittivity and the viscosity is discussed. The validity of the HS equation using strong potentials is assessed. Finally, a model of bulk fluid conductivity is derived. This model allows to take into account the change of local ionic distribution in the vicinity of the mineral. It appears to have a significant impact on the derivation of potentials at low salinities and in the presence of polyvalent counterions.

Description: Extraction of fluids from subsurface reservoirs induces changes in pore pressure, leading not only to geomechanical changes, but also perturbations in seismic velocities and hence observable seismic attributes. Time-lapse seismic analysis can be used to estimate changes in subsurface hydromechanical properties and thus act as a monitoring tool for geological reservoirs. The ability to observe and quantify changes in fluid, stress and strain using seismic techniques has important implications for monitoring risk not only for petroleum applications but also for geological storage of CO 2 and nuclear waste scenarios. In this paper, we integrate hydromechanical simulation results with rock physics models and full-waveform seismic modelling to assess time-lapse seismic attribute resolution for dynamic reservoir characterization and hydromechanical model calibration. The time-lapse seismic simulations use a dynamic elastic reservoir model based on a North Sea deep reservoir undergoing large pressure changes. The time-lapse seismic traveltime shifts and time strains calculated from the modelled and processed synthetic data sets (i.e. pre-stack and post-stack data) are in a reasonable agreement with the true earth models, indicating the feasibility of using 1-D strain rock physics transform and time-lapse seismic processing methodology. Estimated vertical traveltime shifts for the overburden and the majority of the reservoir are within ±1 ms of the true earth model values, indicating that the time-lapse technique is sufficiently accurate for predicting overburden velocity changes and hence geomechanical effects. Characterization of deeper structure below the overburden becomes less accurate, where more advanced time-lapse seismic processing and migration is needed to handle the complex geometry and strong lateral induced velocity changes. Nevertheless, both migrated full-offset pre-stack and near-offset post-stack data image the general features of both the overburden and reservoir units. More importantly, the results from this study indicate that integrated seismic and hydromechanical modelling can help constrain time-lapse uncertainty and hence reduce risk due to fluid extraction and injection.

Description: We study the accuracy and numerical stability of three eigenvector sets for modelling the coupled poroelastic and electromagnetic layered-Earth response. We use a known eigenvector set, its flux-normalized version and a newly derived flux-normalized set. The new set is chosen such that the system is properly uncoupled when the coupling between the poroelastic and electromagnetic fields vanishes. We carry out two different numerical stability tests: the first test focuses on the internal system, eigenvector and eigenvalue consistency; the second test investigates the stability and preciseness of the flux-normalized systems by looking at identity relations. We find that the known set shows the largest deviation for both tests, whereas the new set performs best. In two additional numerical modelling experiments, these numerical inaccuracies are shown to generate numerical noise levels comparable to small signals, such as signals coming from the important interface conversion responses, especially when the coupling coefficient is small. When coupling vanishes completely, the known set does not produce proper results. The new set produces numerically stable and accurate results in all situations. We therefore strongly recommend to use this newly derived set for future layered-Earth seismo-electromagnetic modelling experiments.

Description: The cancer genome is abnormal genome, and the ability to monitor its sequence had undergone a technological revolution. Yet prognosis and diagnosis remain an expert-based decision, with only limited abilities to provide machine-based decisions. We introduce a heterogeneity-based method for stratifying and visualizing whole-genome sequencing (WGS) reads. This method uses the heterogeneity within WGS reads to markedly reduce the dimensionality of next-generation sequencing data; it is available through the tool HiBS (Heterogeneity-Based Subclassification) that allows cancer sample classification. We validated HiBS using 〉200 WGS samples from nine different cancer types from The Cancer Genome Atlas (TCGA). With HiBS, we show progress with two WGS related issues: (i) differentiation between normal (NB) and tumor (TP) samples based solely on the information structure of their WGS data, and (ii) identification of specific regions of chromosomal amplification/deletion and their association with tumor stage. By comparing results to those obtained through available WGS analyses tools, we demonstrate some of the novelties obtained by the approach implemented in HiBS and also show nearly perfect normal/tumor classification, used to identify known and unknown chromosomal aberrations. Finally, the HiBS index has been associated with breast cancer tumor stage.

Description: Recent evidence suggests that many endogenous circular RNAs (circRNAs) may play roles in biological processes. However, the expression patterns and functions of circRNAs in human diseases are not well understood. Computationally identifying circRNAs from total RNA-seq data is a primary step in studying their expression pattern and biological roles. In this work, we have developed a computational pipeline named UROBORUS to detect circRNAs in total RNA-seq data. By applying UROBORUS to RNA-seq data from 46 gliomas and normal brain samples, we detected thousands of circRNAs supported by at least two read counts, followed by successful experimental validation on 24 circRNAs from the randomly selected 27 circRNAs. UROBORUS is an efficient tool that can detect circRNAs with low expression levels in total RNA-seq without RNase R treatment. The circRNAs expression profiling revealed more than 476 circular RNAs differentially expressed in control brain tissues and gliomas. Together with parental gene expression, we found that circRNA and its parental gene have diversified expression patterns in gliomas and control brain tissues. This study establishes an efficient and sensitive approach for predicting circRNAs using total RNA-seq data. The UROBORUS pipeline can be accessed freely for non-commercial purposes at http://uroborus.openbioinformatics.org/ .

Description: Recent studies show that RNA-binding proteins (RBPs) and microRNAs (miRNAs) function in coordination with each other to control post-transcriptional regulation (PTR). Despite this, the majority of research to date has focused on the regulatory effect of individual RBPs or miRNAs. Here, we mapped both RBP and miRNA binding sites on human 3'UTRs and utilized this collection to better understand PTR. We show that the transcripts that lack competition for HuR binding are destabilized more after HuR depletion. We also confirm this finding for PUM1(2) by measuring genome-wide expression changes following the knockdown of PUM1(2) in HEK293 cells. Next, to find potential cooperative interactions, we identified the pairs of factors whose sites co-localize more often than expected by random chance. Upon examining these results for PUM1(2), we found that transcripts where the sites of PUM1(2) and its interacting miRNA form a stem-loop are more stabilized upon PUM1(2) depletion. Finally, using dinucleotide frequency and counts of regulatory sites as features in a regression model, we achieved an AU-ROC of 0.86 in predicting mRNA half-life in BEAS-2B cells. Altogether, our results suggest that future studies of PTR must consider the combined effects of RBPs and miRNAs, as well as their interactions.

Description: Annotation of protein-coding genes is very important in bioinformatics and biology and has a decisive influence on many downstream analyses. Homology-based gene prediction programs allow for transferring knowledge about protein-coding genes from an annotated organism to an organism of interest. Here, we present a homology-based gene prediction program called GeMoMa. GeMoMa utilizes the conservation of intron positions within genes to predict related genes in other organisms. We assess the performance of GeMoMa and compare it with state-of-the-art competitors on plant and animal genomes using an extended best reciprocal hit approach. We find that GeMoMa often makes more precise predictions than its competitors yielding a substantially increased number of correct transcripts. Subsequently, we exemplarily validate GeMoMa predictions using Sanger sequencing. Finally, we use RNA-seq data to compare the predictions of homology-based gene prediction programs, and find again that GeMoMa performs well. Hence, we conclude that exploiting intron position conservation improves homology-based gene prediction, and we make GeMoMa freely available as command-line tool and Galaxy integration.

Description: The Quaternary Añavieja-Dévanos tufa system is located in the northern sector of the Iberian Chain. It has been previously tackled by means sedimentological studies focused on the available outcrops and some boreholes. They have permitted the proposal of a sedimentary scenario that fits with a pool-barrage fluvial tufa model. However a better knowledge of the characteristics and internal distribution of the usually non-outcropping pool deposits as well as of its relationship with barrage deposits has not been evaluated in detail yet. Palaeoenvironmental studies on tufas are usually biased because tufas are commonly delicate facies exposed to intense erosion during water level fall stages; for this reason outcrops are usually scarce and very often coincide with the most cemented barrage deposits. In order to analyse the internal characteristics of the tufa deposits under study, but also the lateral correlation among different facies, ground penetrating radar (GPR) has been employed both for the evaluation of its applicability in such kind of environments and to improve, if possible, the sedimentary model using geophysical data in sectors without outcrops. A GPR survey including different antennas ranging from 50 to 500 MHz along different sectors and its comparison with natural outcrops has been carried out. GPR results have permitted to deduce clear differences between pool and barrage deposits and to recognise its internal structure and geometrical relationships. The survey also permitted an approach to different scales of heterogeneities in the radarfacies evaluation by using distinct antennas and therefore, reaching different resolutions and penetrations. The resulting integration from different antennas allows three different attenuant and eight reflective radarfacies to be defined permitting a better approach to the real extension of the pool areas. These results have permitted to decipher the horizontal and vertical facies changes and the identification of a scarcer development of pool deposits than expected in the studied system.

Description: CircRNAs are novel members of the non-coding RNA family. For several decades circRNAs have been known to exist, however only recently the widespread abundance has become appreciated. Annotation of circRNAs depends on sequencing reads spanning the backsplice junction and therefore map as non-linear reads in the genome. Several pipelines have been developed to specifically identify these non-linear reads and consequently predict the landscape of circRNAs based on deep sequencing datasets. Here, we use common RNAseq datasets to scrutinize and compare the output from five different algorithms; circRNA_finder, find_circ, CIRCexplorer, CIRI, and MapSplice and evaluate the levels of bona fide and false positive circRNAs based on RNase R resistance. By this approach, we observe surprisingly dramatic differences between the algorithms specifically regarding the highly expressed circRNAs and the circRNAs derived from proximal splice sites. Collectively, this study emphasizes that circRNA annotation should be handled with care and that several algorithms should ideally be combined to achieve reliable predictions.

Description: Two novel transient controlled source electromagnetic methods called circular electrical dipole (CED) and differential electrical dipole (DED) are theoretically analysed for applications in shallow marine environments. 1-D and 3-D time-domain modelling studies are used to investigate the detectability and applicability of the methods when investigating resistive layers/targets representing hydrocarbon-saturated formations. The results are compared to the conventional time-domain horizontal electrical dipole (HED) and vertical electrical dipole (VED) sources. The applied theoretical modelling studies demonstrate that CED and DED have higher signal detectability towards resistive targets compared to TD-CSEM, but demonstrate significantly poorer signal amplitudes. Future CED/DED applications will have to solve this issue prior to measuring. Furthermore, the two novel methods have very similar detectability characteristics towards 3-D resistive targets embedded in marine sediments as VED while being less susceptible towards non-verticality. Due to the complex transmitter design of CED/DED the systems are prone to geometrical errors. Modelling studies show that even small transmitter inaccuracies have strong effects on the signal characteristics of CED making an actual marine application difficult at the present time. In contrast, the DED signal is less affected by geometrical errors in comparison to CED and may therefore be more adequate for marine applications.

Description: An L-configured, three-component short period seismic array was deployed on the Ross Ice Shelf, Antarctica during November 2014. Polarization analysis of ambient noise data from these stations shows linearly polarized waves for frequency bands between 0.2 and 2 Hz. A spectral peak at about 1.6 Hz is interpreted as the resonance frequency of the water column and is used to estimate the water layer thickness below the ice shelf. The frequency band from 4 to 18 Hz is dominated by Rayleigh and Love waves propagating from the north that, based on daily temporal variations, we conclude were generated by field camp activity. Frequency–slowness plots were calculated using beamforming. Resulting Love and Rayleigh wave dispersion curves were inverted for the shear wave velocity profile within the firn and ice to ~150 m depth. The derived density profile allows estimation of the pore close-off depth and the firn–air content thickness. Separate inversions of Rayleigh and Love wave dispersion curves give different shear wave velocity profiles within the firn. We attribute this difference to an effective anisotropy due to fine layering. The layered structure of firn, ice, water and the seafloor results in a characteristic dispersion curve below 7 Hz. Forward modelling the observed Rayleigh wave dispersion curves using representative firn, ice, water and sediment structures indicates that Rayleigh waves are observed when wavelengths are long enough to span the distance from the ice shelf surface to the seafloor. The forward modelling shows that analysis of seismic data from an ice shelf provides the possibility of resolving ice shelf thickness, water column thickness and the physical properties of the ice shelf and underlying seafloor using passive-source seismic data.

Description: We present an algorithm to recover the Bayesian posterior model probability density function of subsurface elastic parameters, as required by the full pressure field recorded at an ocean bottom cable due to an impulsive seismic source. Both the data noise and source wavelet are estimated by our algorithm, resulting in robust estimates of subsurface velocity and density. In contrast to purely gradient based approaches, our method avoids model regularization entirely and produces an ensemble of models that can be visualized and queried to provide meaningful information about the sensitivity of the data to the subsurface, and the level of resolution of model parameters. Our algorithm is trans-dimensional and performs model selection, sampling over a wide range of model parametrizations. We follow a frequency domain approach and derive the corresponding likelihood in the frequency domain. We present first a synthetic example of a reservoir at 2 km depth with minimal acoustic impedance contrast, which is difficult to study with conventional seismic amplitude versus offset changes. Finally, we apply our methodology to survey data collected over the Alba field in the North Sea, an area which is known to show very little lateral heterogeneity but nevertheless presents challenges for conventional post migration seismic amplitude versus offset analysis.

Description: Background: Fusion transcripts are formed by either fusion genes (DNA level) or trans-splicing events (RNA level). They have been recognized as a promising tool for diagnosing, subtyping and treating cancers. RNA-seq has become a precise and efficient standard for genome-wide screening of such aberration events. Many fusion transcript detection algorithms have been developed for paired-end RNA-seq data but their performance has not been comprehensively evaluated to guide practitioners. In this paper, we evaluated 15 popular algorithms by their precision and recall trade-off, accuracy of supporting reads and computational cost. We further combine top-performing methods for improved ensemble detection. Results: Fifteen fusion transcript detection tools were compared using three synthetic data sets under different coverage, read length, insert size and background noise, and three real data sets with selected experimental validations. No single method dominantly performed the best but SOAPfuse generally performed well, followed by FusionCatcher and JAFFA. We further demonstrated the potential of a meta-caller algorithm by combining top performing methods to re-prioritize candidate fusion transcripts with high confidence that can be followed by experimental validation. Conclusion: Our result provides insightful recommendations when applying individual tool or combining top performers to identify fusion transcript candidates.

Description: A novel application of seismic interferometry (SI) and Marchenko imaging using both surface and borehole data is presented. A series of redatuming schemes is proposed to combine both data sets for robust deep local imaging in the presence of velocity uncertainties. The redatuming schemes create a virtual acquisition geometry where both sources and receivers lie at the horizontal borehole level, thus only a local velocity model near the borehole is needed for imaging, and erroneous velocities in the shallow area have no effect on imaging around the borehole level. By joining the advantages of SI and Marchenko imaging, a macrovelocity model is no longer required and the proposed schemes use only single-component data. Furthermore, the schemes result in a set of virtual data that have fewer spurious events and internal multiples than previous virtual source redatuming methods. Two numerical examples are shown to illustrate the workflow and to demonstrate the benefits of the method. One is a synthetic model and the other is a realistic model of a field in the North Sea. In both tests, improved local images near the boreholes are obtained using the redatumed data without accurate velocities, because the redatumed data are close to the target.

Description: Regulatory DNA elements, short genomic segments that regulate gene expression, have been implicated in developmental disorders and human disease. Despite this clinical urgency, only a small fraction of the regulatory DNA repertoire has been confirmed through reporter gene assays. The overall success rate of functional validation of candidate regulatory elements is low. Moreover, the number and diversity of datasets from which putative regulatory elements can be identified is large and rapidly increasing. We generated a flexible and user-friendly tool to integrate the information from different types of genomic datasets, e.g. ATAC-seq, ChIP-seq, conservation, aiming to increase the ease and success rate of functional prediction. To this end, we developed the EMERGE program that merges all datasets that the user considers informative and uses a logistic regression framework, based on validated functional elements, to set optimal weights to these datasets. ROC curve analysis shows that a combination of datasets leads to improved prediction of tissue-specific enhancers in human, mouse and Drosophila genomes. Functional assays based on this prediction can be expected to have substantially higher success rates. The resulting integrated signal for prediction of functional elements can be plotted in a build-in genome browser or exported for further analysis.

Description: Regulation of gene expression requires both transcription factor (TFs) and epigenetic modifications, and interplays between the two types of factors have been discovered. However study of relationships between chromatin features and TF–TF co-occupancy remains limited. Here, we revealed the relationship by first illustrating distinct profile patterns of chromatin features related to different binding events, including single TF binding and TF–TF co-occupancy of 71 TFs from five human cell lines. We further implemented statistical analyses to demonstrate the relationship by accurately predicting co-occupancy genome-widely using chromatin features including DNase I hypersensitivity, 11 histone modifications (HMs) and GC content. Remarkably, our results showed that the combination of chromatin features enables accurate predictions across the five cells. For individual chromatin features, DNase I enables high and consistent predictions. H3K27ac, H3K4me 2, H3K4me3 and H3K9ac are more reliable predictors than other HMs. Although the combination of 11 HMs achieves accurate predictions, their predictive ability varies considerably when a model obtained from one cell is applied to others, indicating relationship between HMs and TF–TF co-occupancy is cell type dependent. GC content is not a reliable predictor, but the addition of GC content to any other features enhances their predictive ability. Together, our results elucidate a strong relationship between TF–TF co-occupancy and chromatin features.

Description: The spatial organization of the genome influences cellular function, notably gene regulation. Recent studies have assessed the three-dimensional (3D) co-localization of functional annotations (e.g. centromeres, long terminal repeats) using 3D genome reconstructions from Hi-C (genome-wide chromosome conformation capture) data; however, corresponding assessments for continuous functional genomic data (e.g. chromatin immunoprecipitation-sequencing (ChIP-seq) peak height) are lacking. Here, we demonstrate that applying bump hunting via the patient rule induction method (PRIM) to ChIP-seq data superposed on a Saccharomyces cerevisiae 3D genome reconstruction can discover ‘functional 3D hotspots’, regions in 3-space for which the mean ChIP-seq peak height is significantly elevated. For the transcription factor Swi6, the top hotspot by P -value contains MSB2 and ERG11 – known Swi6 target genes on different chromosomes. We verify this finding in a number of ways. First, this top hotspot is relatively stable under PRIM across parameter settings. Second, this hotspot is among the top hotspots by mean outcome identified by an alternative algorithm, k -Nearest Neighbor ( k -NN) regression. Third, the distance between MSB2 and ERG11 is smaller than expected (by resampling) in two other 3D reconstructions generated via different normalization and reconstruction algorithms. This analytic approach can discover functional 3D hotspots and potentially reveal novel regulatory interactions.

Description: Hidden Markov models (HMMs) have been extensively used to dissect the genome into functionally distinct regions using data such as RNA expression or DNA binding measurements. It is a challenge to disentangle processes occurring on complementary strands of the same genomic region. We present the double-stranded HMM (dsHMM), a model for the strand-specific analysis of genomic processes. We applied dsHMM to yeast using strand specific transcription data, nucleosome data, and protein binding data for a set of 11 factors associated with the regulation of transcription.The resulting annotation recovers the mRNA transcription cycle (initiation, elongation, termination) while correctly predicting strand-specificity and directionality of the transcription process. We find that pre-initiation complex formation is an essentially undirected process, giving rise to a large number of bidirectional promoters and to pervasive antisense transcription. Notably, 12% of all transcriptionally active positions showed simultaneous activity on both strands. Furthermore, dsHMM reveals that antisense transcription is specifically suppressed by Nrd1, a yeast termination factor.

Description: Chromatin immunoprecipitation with massively parallel sequencing (ChIP-seq) is widely used to identify binding sites for a target protein in the genome. An important scientific application is to identify changes in protein binding between different treatment conditions, i.e. to detect differential binding. This can reveal potential mechanisms through which changes in binding may contribute to the treatment effect. The csaw package provides a framework for the de novo detection of differentially bound genomic regions. It uses a window-based strategy to summarize read counts across the genome. It exploits existing statistical software to test for significant differences in each window. Finally, it clusters windows into regions for output and controls the false discovery rate properly over all detected regions. The csaw package can handle arbitrarily complex experimental designs involving biological replicates. It can be applied to both transcription factor and histone mark datasets, and, more generally, to any type of sequencing data measuring genomic coverage. csaw performs favorably against existing methods for de novo DB analyses on both simulated and real data. csaw is implemented as a R software package and is freely available from the open-source Bioconductor project.

Description: Incremental selection within a population, defined as limited fitness changes following mutation, is an important aspect of many evolutionary processes. Strongly advantageous or deleterious mutations are detected using the synonymous to non-synonymous mutations ratio. However, there are currently no precise methods to estimate incremental selection. We here provide for the first time such a detailed method and show its precision in multiple cases of micro-evolution. The proposed method is a novel mixed lineage tree/sequence based method to detect within population selection as defined by the effect of mutations on the average number of offspring. Specifically, we propose to measure the log of the ratio between the number of leaves in lineage trees branches following synonymous and non-synonymous mutations. The method requires a high enough number of sequences, and a large enough number of independent mutations. It assumes that all mutations are independent events. It does not require of a baseline model and is practically not affected by sampling biases. We show the method's wide applicability by testing it on multiple cases of micro-evolution. We show that it can detect genes and inter-genic regions using the selection rate and detect selection pressures in viral proteins and in the immune response to pathogens.

Description: An important challenge in cancer genomics is precise detection of structural variations (SVs) by high-throughput short-read sequencing, which is hampered by the high false discovery rates of existing analysis tools. Here, we propose an accurate SV detection method named COSMOS, which compares the statistics of the mapped read pairs in tumor samples with isogenic normal control samples in a distinct asymmetric manner. COSMOS also prioritizes the candidate SVs using strand-specific read-depth information. Performance tests on modeled tumor genomes revealed that COSMOS outperformed existing methods in terms of F-measure. We also applied COSMOS to an experimental mouse cell-based model, in which SVs were induced by genome engineering and gamma-ray irradiation, followed by polymerase chain reaction-based confirmation. The precision of COSMOS was 84.5%, while the next best existing method was 70.4%. Moreover, the sensitivity of COSMOS was the highest, indicating that COSMOS has great potential for cancer genome analysis.

Description: The effect of the selection of different nuclear magnetic resonance (NMR) relaxation times for permeability estimation is investigated for a set of fully brine-saturated rocks acquired from Cretaceous carbonate reservoirs in the North Sea and Middle East. Estimators that are obtained from the relaxation times based on the Pythagorean means are compared with estimators that are obtained from the relaxation times based on the concept of a cumulative saturation cut-off. Select portions of the longitudinal ( T 1 ) and transverse ( T 2 ) relaxation-time distributions are systematically evaluated by applying various cut-offs, analogous to the Winland-Pittman approach for mercury injection capillary pressure (MICP) curves. Finally, different approaches to matching the NMR and MICP distributions using different mean-based scaling factors are validated based on the performance of the related size-scaled estimators. The good results that were obtained demonstrate possible alternatives to the commonly adopted logarithmic mean estimator and reinforce the importance of NMR-MICP integration to improving carbonate permeability estimates.

Description: Static time-delay corrections are frequency independent and ignore velocity variations away from the assumed vertical ray path through the subsurface. There is therefore a clear potential for improvement if the finite frequency nature of wave propagation can be properly accounted for. Such a method is presented here based on the Born approximation, the assumption of surface consistency and the misfit of instantaneous phase. The concept of instantaneous phase lends itself very well for sweep-like signals, hence these are the focus of this study. Analytical sensitivity kernels are derived that accurately predict frequency-dependent phase shifts due to P -wave anomalies in the near surface. They are quick to compute and robust near the source and receivers. An additional correction is presented that re-introduces the nonlinear relation between model perturbation and phase delay, which becomes relevant for stronger velocity anomalies. The phase shift as function of frequency is a slowly varying signal, its computation therefore does not require fine sampling even for broad-band sweeps. The kernels reveal interesting features of the sensitivity of seismic arrivals to the near surface: small anomalies can have a relative large impact resulting from the medium field term that is dominant near the source and receivers. Furthermore, even simple velocity anomalies can produce a distinct frequency-dependent phase behaviour. Unlike statics, the predicted phase corrections are smooth in space. Verification with spectral element simulations shows an excellent match for the predicted phase shifts over the entire seismic frequency band. Applying the phase shift to the reference sweep corrects for wavelet distortion, making the technique akin to surface consistent deconvolution, even though no division in the spectral domain is involved. As long as multiple scattering is mild, surface consistent finite frequency phase corrections outperform traditional statics for moderately large velocity contrasts, also in the case of a free surface with topography. The kernels could also be used to update the velocity model, if one has knowledge of (wave propagation related only) surface consistent phase operators.

Description: The seislet transform has been demonstrated to have a better compression performance for seismic data compared with other well-known sparsity promoting transforms, thus it can be used to remove random noise by simply applying a thresholding operator in the seislet domain. Since the seislet transform compresses the seismic data along the local structures, the seislet thresholding can be viewed as a simple structural filtering approach. Because of the dependence on a precise local slope estimation, the seislet transform usually suffers from low compression ratio and high reconstruction error for seismic profiles that have dip conflicts. In order to remove the limitation of seislet thresholding in dealing with conflicting-dip data, I propose a dip-separated filtering strategy. In this method, I first use an adaptive empirical mode decomposition based dip filter to separate the seismic data into several dip bands (5 or 6). Next, I apply seislet thresholding to each separated dip component to remove random noise. Then I combine all the denoised components to form the final denoised data. Compared with other dip filters, the empirical mode decomposition based dip filter is data-adaptive. One only needs to specify the number of dip components to be separated. Both complicated synthetic and field data examples show superior performance of my proposed approach than the traditional alternatives. The dip-separated structural filtering is not limited to seislet thresholding, and can also be extended to all those methods that require slope information.

Description: Noise interferometry is the process by which approximations to acoustic Green's functions, which describe sound propagation between two locations, are estimated by cross-correlating time series of ambient noise measured at those locations. Noise-interferometry-based approximations to Green's functions can be used as the basis for a variety of inversion algorithms, thereby providing a purely passive alternative to active-source ocean acoustic remote sensing. In this paper we give an overview of results from noise interferometry experiments conducted in the Florida Straits at 100 m depth in December 2012, and at 600 m depth in September/October 2013. Under good conditions for noise interferometry, estimates of cross-correlation functions are shown to allow one to perform advanced phase-coherent signal processing techniques to perform waveform inversions, estimate currents by exploiting non-reciprocity, perform time-reversal/back-propagation calculations and investigate modal dispersion using time-warping techniques. Conditions which are favourable for noise interferometry are identified and discussed.

Description: In this paper, we consider a new spectral finite volume method (FVM) for the elastic wave equations. Our new FVM is based on a piecewise constant approximation on a fine mesh and a high-order polynomial reconstruction on a coarser mesh. Our new method is constructed based on two existing techniques, the high-order FVM and the spectral FVM. In fact, we will construct a new method to take advantage of both methods. More precisely, our method has two distinctive features. The first one is that the local polynomial reconstructions are performed on the coarse triangles and the reconstruction matrices for all the coarse triangles are the same. This fact enhances the parallelization of our algorithm. We will present a parallel implementation of our method and show excellent efficiency results. The second one is that, by using a suitable number of finer triangles with a coarse triangle, we obtain an overdetermined reconstruction system, which can enhance the robustness of the reconstruction process. To derive our scheme, standard finite volume technique is applied to each fine triangle, and the high-order reconstructed polynomials, computed on coarse triangles, are used to compute numerical fluxes. We will present numerical results to show the performance of our method. Our method is presented for 2-D problems, but the same methodology can be applied to 3-D.

Description: At the heart of the full waveform inversion (FWI) implementation is wavefield extrapolation, and specifically its accuracy and cost. To obtain accurate, dispersion free wavefields, the extrapolation for modelling is often expensive. Combining an efficient extrapolation with a novel gradient preconditioning can render an FWI implementation that efficiently converges to an accurate model. We, specifically, recast the extrapolation part of the inversion in terms of its spectral components for both data and gradient calculation. This admits dispersion free wavefields even at large extrapolation time steps, which improves the efficiency of the inversion. An alternative spectral representation of the depth axis in terms of sine functions allows us to impose a free surface boundary condition, which reflects our medium boundaries more accurately. Using a newly derived perfectly matched layer formulation for this spectral implementation, we can define a finite model with absorbing boundaries. In order to reduce the nonlinearity in FWI, we propose a multiscale conditioning of the objective function through combining the different directional components of the gradient to optimally update the velocity. Through solving a simple optimization problem, it specifically admits the smoothest approximate update while guaranteeing its ascending direction. An application to the Marmousi model demonstrates the capability of the proposed approach and justifies our assertions with respect to cost and convergence.

Description: Small non-coding RNAs play a key role in many physiological and pathological processes. Since 2004, miRNA sequences have been catalogued in miRBase, which is currently in its 21st version. We investigated sequence and structural features of miRNAs annotated in the miRBase and compared them between different versions of this reference database. We have identified that the two most recent releases (v20 and v21) are influenced by next-generation sequencing based miRNA predictions and show significant deviation from miRNAs discovered prior to the high-throughput profiling period. From the analysis of miRBase, we derived a set of key characteristics to predict new miRNAs and applied the implemented algorithm to evaluate novel blood-borne miRNA candidates. We carried out 705 individual whole miRNA sequencings of blood cells and collected a total of 9.7 billion reads. Using miRDeep2 we initially predicted 1452 potentially novel miRNAs. After excluding false positives, 518 candidates remained. These novel candidates were ranked according to their distance to the features in the early miRBase versions allowing for an easier selection of a subset of putative miRNAs for validation. Selected candidates were successfully validated by qRT-PCR and northern blotting. In addition, we implemented a web-server for ranking potential miRNA candidates, which is available at: www.ccb.uni-saarland.de/novomirank .

Description: Spectral induced polarization (SIP) data are commonly analysed using phenomenological models. Among these models the Cole–Cole (CC) model is the most popular choice to describe the strength and frequency dependence of distinct polarization peaks in the data. More flexibility regarding the shape of the spectrum is provided by decomposition schemes. Here the spectral response is decomposed into individual responses of a chosen elementary relaxation model, mathematically acting as kernel in the involved integral, based on a broad range of relaxation times. A frequently used kernel function is the Debye model, but also the CC model with some other a priorly specified frequency dispersion (e.g. Warburg model) has been proposed as kernel in the decomposition. The different decomposition approaches in use, also including conductivity and resistivity formulations, pose the question to which degree the integral spectral parameters typically derived from the obtained relaxation time distribution are biased by the approach itself. Based on synthetic SIP data sampled from an ideal CC response, we here investigate how the two most important integral output parameters deviate from the corresponding CC input parameters. We find that the total chargeability may be underestimated by up to 80 per cent and the mean relaxation time may be off by up to three orders of magnitude relative to the original values, depending on the frequency dispersion of the analysed spectrum and the proximity of its peak to the frequency range limits considered in the decomposition. We conclude that a quantitative comparison of SIP parameters across different studies, or the adoption of parameter relationships from other studies, for example when transferring laboratory results to the field, is only possible on the basis of a consistent spectral analysis procedure. This is particularly important when comparing effective CC parameters with spectral parameters derived from decomposition results.

Description: Viability for the development of an engineered geothermal system (EGS) in the oilsands region near Fort McMurray, Alberta, is investigated by studying the structure of the Precambrian basement rocks with magnetotellurics (MT). MT data were collected at 94 broad-band stations on two east–west profiles. Apparent resistivity and phase data showed little variation along each profile. The short period MT data detected a 1-D resistivity structure that could be identified as the shallow sedimentary basin underlain by crystalline basement rocks to a depth of 4–5 km. At lower frequencies a strong directional dependence, large phase splits, and regions of out-of-quadrant (OOQ) phase were detected. 2-D isotropic inversions of these data failed to produce a realistic resistivity model. A detailed dimensionality analysis found links between large phase tensor skews (~15°), azimuths, OOQ phases and tensor decomposition strike angles at periods greater than 1 s. Low magnitude induction vectors, as well as uniformity of phase splits and phase tensor character between the northern and southern profiles imply that a 3-D analysis is not necessary or appropriate. Therefore, 2-D anisotropic forward modelling was used to generate a resistivity model to interpret the MT data. The preferred model was based on geological observations of outcropping anisotropic mylonitic basement rocks of the Charles Lake shear zone, 150 km to the north, linked to the study area by aeromagnetic and core sample data. This model fits all four impedance tensor elements with an rms misfit of 2.82 on the southern profile, and 3.3 on the northern. The conductive phase causing the anisotropy is interpreted to be interconnected graphite films within the metamorphic basement rocks. Characterizing the anisotropy is important for understanding how artificial fractures, necessary for EGS development, would form. Features of MT data commonly interpreted to be 3-D (e.g. out of OOQ phase and large phase tensor skew) are shown to be interpretable with this 2-D anisotropic model.

Description: The identification of genes with specific patterns of change (e.g. down-regulated and methylated) as phenotype drivers or samples with similar profiles for a given gene set as drivers of clinical outcome, requires the integration of several genomic data types for which an ‘integrate by intersection’ (IBI) approach is often applied. In this approach, results from separate analyses of each data type are intersected, which has the limitation of a smaller intersection with more data types. We introduce a new method, GISPA (Gene Integrated Set Profile Analysis) for integrated genomic analysis and its variation, SISPA (Sample Integrated Set Profile Analysis) for defining respective genes and samples with the context of similar, a priori specified molecular profiles. With GISPA, the user defines a molecular profile that is compared among several classes and obtains ranked gene sets that satisfy the profile as drivers of each class. With SISPA, the user defines a gene set that satisfies a profile and obtains sample groups of profile activity. Our results from applying GISPA to human multiple myeloma (MM) cell lines contained genes of known profiles and importance, along with several novel targets, and their further SISPA application to MM coMMpass trial data showed clinical relevance.

Description: The contribution of different mechanisms to the regulation of gene expression varies for different tissues and tumors. Complementation of predicted mRNA–miRNA and gene–transcription factor (TF) relationships with the results of expression correlation analyses derived for specific tumor types outlines the interactions with functional impact in the current biomaterial. We developed CrossHub software, which enables two-way identification of most possible TF–gene interactions: on the basis of ENCODE ChIP-Seq binding evidence or Jaspar prediction and co-expression according to the data of The Cancer Genome Atlas (TCGA) project, the largest cancer omics resource. Similarly, CrossHub identifies mRNA–miRNA pairs with predicted or validated binding sites (TargetScan, mirSVR, PicTar, DIANA microT, miRTarBase) and strong negative expression correlations. We observed partial consistency between ChIP-Seq or miRNA target predictions and gene–TF/miRNA co-expression, demonstrating a link between these indicators. Additionally, CrossHub expression-methylation correlation analysis can be used to identify hypermethylated CpG sites or regions with the greatest potential impact on gene expression. Thus, CrossHub is capable of outlining molecular portraits of a specific gene and determining the three most common sources of expression regulation: promoter/enhancer methylation, miRNA interference and TF-mediated activation or repression. CrossHub generates formatted Excel workbooks with the detailed results. CrossHub is freely available at https://sourceforge.net/projects/crosshub/ .

Description: Deep geological repositories, isolated from the geosphere by an engineered bentonite barrier, are currently considered the safest solution for high-level radioactive waste (HLRW) disposal. As the physical conditions and properties of the bentonite barrier are anticipated to change with time, seismic tomography was suggested as a viable technique to monitor the physical state and integrity of the barrier and to timely detect any unforeseen failure. To do so, the seismic monitoring system needs to be optimized, and this can be achieved by conducting numerical simulations of wave propagation in the repository geometry. Previous studies treated bentonite as an elastic medium, whereas recent experimental investigations indicate its pronounced viscoelastic behaviour. The aims of this contribution are (i) to numerically estimate the effective attenuation of bentonite as a function of temperature T and water content W c , so that synthetic data can accurately reproduce experimental traces and (ii) assess the feasibility and limitation of the HLRW repository monitoring by simulating the propagation of sonic waves in a realistic repository geometry. A finite difference method was utilized to simulate the wave propagation in experimental and repository setups. First, the input of the viscoelastic model was varied to achieve a match between experimental and numerical traces. The routine was repeated for several values of W c and T , so that quality factors Q p ( W c , T ) and Q s ( W c , T ) were obtained. Then, the full-scale monitoring procedure was simulated for six scenarios, representing the evolution of bentonite's physical state. The estimated Q p and Q s exhibited a minimum at W c = 20 per cent and higher sensitivity to W c , rather than T , suggesting that pronounced inelasticity of the clay has to be taken into account in geophysical modelling and analysis. The repository-model traces confirm that active seismic monitoring is, in principle, capable of depicting physical changes in the bentonite barrier. However, the locations of sources and receivers relative to the tunnel need to be optimized to achieve best sensitivity to the changes. It was also observed that first arrivals do not necessarily represent the most informative part of the signal; thus the time windows of the analysis need to be selected, accounting for the geometry of the acquisition system. This contribution should be considered as a next step towards the development of a numerical approach to aid in the design and optimization of a non-intrusive monitoring system in HLRW repositories.

Description: Variations in self-potentials (SP) measured at surface during pumping of a heterogeneous confined fractured rock aquifer have been monitored and modelled in order to investigate capabilities and limitations of SP methods in estimating aquifer hydraulic properties. SP variations were recorded around a pumping well using an irregular grid of 31 non-polarizing Pb-PbCl 2 that were referenced to a remote electrode and connected to a commercial multiplexer and digitizer/data logger through a passive lowpass filter on each channel. The lowpass filter reduced noise by a factor of 10 compared to levels obtained using the data logger's integration-based sampling method for powerline noise suppression alone. SP signals showed a linear relationship with water levels observed in the pumping and monitoring wells over the pumping period, with an apparent electrokinetic coupling coefficient of –3.4 mV · m –1 . Following recent developments in SP methodology, variability of the SP response between different electrodes is taken as a proxy for lateral variations in hydraulic head within the aquifer and used to infer lateral variations in the aquifer's apparent transmissivity. In order to demonstrate the viability of this approach, SP is modelled numerically to determine its sensitivity to (i) lateral variations in the hydraulic conductivity of the confined aquifer and (ii) the electrical conductivity of the confining layer and conductive well casing. In all cases, SP simulated on the surface still varies linearly with hydraulic head modelled at the base on the confining layer although the apparent coupling coefficient changes to varying degrees. Using the linear relationship observed in the field, drawdown curves were inferred for each electrode location using SP variations observed over the duration of the pumping period. Transmissivity estimates, obtained by fitting the Theis model to inferred drawdown curves at all 31 electrodes, fell within a narrow range of (2.0–4.2) x 10 –3 m 2 · s –1 and were consistent with values measured in the pumping and monitoring wells. This approach will be of particular interest where monitoring wells are lacking for direct measurement, and SP on the surface can be used to quickly estimate hydraulic properties.

Description: We present a numerical algorithm for 3-D electromagnetic (EM) simulations in conducting media with general electric anisotropy. The algorithm is based on the finite-difference discretization of frequency-domain Maxwell's equations on a Lebedev grid, in which all components of the electric field are collocated but half a spatial step staggered with respect to the magnetic field components, which also are collocated. This leads to a system of linear equations that is solved using a stabilized biconjugate gradient method with a multigrid preconditioner. We validate the accuracy of the numerical results for layered and 3-D tilted transverse isotropic (TTI) earth models representing typical scenarios used in the marine controlled-source EM method. It is then demonstrated that not taking into account the full anisotropy of the conductivity tensor can lead to misleading inversion results. For synthetic data corresponding to a 3-D model with a TTI anticlinal structure, a standard vertical transverse isotropic (VTI) inversion is not able to image a resistor, while for a 3-D model with a TTI synclinal structure it produces a false resistive anomaly. However, if the VTI forward solver used in the inversion is replaced by the proposed TTI solver with perfect knowledge of the strike and dip of the dipping structures, the resulting resistivity images become consistent with the true models.

Description: Single-cell gene expression data provide invaluable resources for systematic characterization of cellular hierarchy in multi-cellular organisms. However, cell lineage reconstruction is still often associated with significant uncertainty due to technological constraints. Such uncertainties have not been taken into account in current methods. We present ECLAIR (Ensemble Cell Lineage Analysis with Improved Robustness), a novel computational method for the statistical inference of cell lineage relationships from single-cell gene expression data. ECLAIR uses an ensemble approach to improve the robustness of lineage predictions, and provides a quantitative estimate of the uncertainty of lineage branchings. We show that the application of ECLAIR to published datasets successfully reconstructs known lineage relationships and significantly improves the robustness of predictions. ECLAIR is a powerful bioinformatics tool for single-cell data analysis. It can be used for robust lineage reconstruction with quantitative estimate of prediction accuracy.

Description: We develop a procedure to invert time domain induced polarization (IP) data for inductive sources. Our approach is based upon the inversion methodology in conventional electrical IP (EIP), which uses a sensitivity function that is independent of time. However, significant modifications are required for inductive source IP (ISIP) because electric fields in the ground do not achieve a steady state. The time-history for these fields needs to be evaluated and then used to define approximate IP currents. The resultant data, either a magnetic field or its derivative, are evaluated through the Biot-Savart law. This forms the desired linear relationship between data and pseudo-chargeability. Our inversion procedure has three steps: (1) Obtain a 3-D background conductivity model. We advocate, where possible, that this be obtained by inverting early-time data that do not suffer significantly from IP effects. (2) Decouple IP responses embedded in the observations by forward modelling the TEM data due to a background conductivity and subtracting these from the observations. (3) Use the linearized sensitivity function to invert data at each time channel and recover pseudo-chargeability. Post-interpretation of the recovered pseudo-chargeabilities at multiple times allows recovery of intrinsic Cole-Cole parameters such as time constant and chargeability. The procedure is applicable to all inductive source survey geometries but we focus upon airborne time domain EM (ATEM) data with a coincident-loop configuration because of the distinctive negative IP signal that is observed over a chargeable body. Several assumptions are adopted to generate our linearized modelling but we systematically test the capability and accuracy of the linearization for ISIP responses arising from different conductivity structures. On test examples we show: (1) our decoupling procedure enhances the ability to extract information about existence and location of chargeable targets directly from the data maps; (2) the horizontal location of a target body can be well recovered through inversion; (3) the overall geometry of a target body might be recovered but for ATEM data a depth weighting is required in the inversion; (4) we can recover estimates of intrinsic and that may be useful for distinguishing between two chargeable targets.

Description: The extraction of spectral information in the inversion process of time-domain (TD) induced polarization (IP) data is changing the use of the TDIP method. Data interpretation is evolving from a qualitative description of the subsurface, able only to discriminate the presence of contrasts in chargeability parameters, towards a quantitative analysis of the investigated media, which allows for detailed soil- and rock-type characterization. Two major limitations restrict the extraction of the spectral information of TDIP data in the field: (i) the difficulty of acquiring reliable early-time measurements in the millisecond range and (ii) the self-potential background drift in the measured potentials distorting the shape of the late-time IP responses, in the second range. Recent developments in TDIP acquisition equipment have given access to full-waveform recordings of measured potentials and transmitted current, opening for a breakthrough in data processing. For measuring at early times, we developed a new method for removing the significant noise from power lines contained in the data through a model-based approach, localizing the fundamental frequency of the power-line signal in the full-waveform IP recordings. By this, we cancel both the fundamental signal and its harmonics. Furthermore, an efficient processing scheme for identifying and removing spikes in TDIP data was developed. The noise cancellation and the de-spiking allow the use of earlier and narrower gates, down to a few milliseconds after the current turn-off. In addition, tapered windows are used in the final gating of IP data, allowing the use of wider and overlapping gates for higher noise suppression with minimal distortion of the signal. For measuring at late times, we have developed an algorithm for removal of the self-potential drift. Usually constant or linear drift-removal algorithms are used, but these algorithms often fail in removing the background potentials present when the electrodes used for potential readings are previously used for current injection, also for simple contact resistance measurements. We developed a drift-removal scheme that models the polarization effect and efficiently allows for preserving the shape of the IP responses at late times. Uncertainty estimates are essential in the inversion of IP data. Therefore, in the final step of the data processing, we estimate the data standard deviation based on the data variability within the IP gates and the misfit of the background drift removal Overall, the removal of harmonic noise, spikes, self-potential drift, tapered windowing and the uncertainty estimation allows for doubling the usable range of TDIP data to almost four decades in time (corresponding to four decades in frequency), which will significantly advance the applicability of the IP method.

Description: The quantification of transcriptomic features is the basis of the analysis of RNA-seq data. We present an integrated alignment workflow and a simple counting-based approach to derive estimates for gene, exon and exon–exon junction expression. In contrast to previous counting-based approaches, EQP takes into account only reads whose alignment pattern agrees with the splicing pattern of the features of interest. This leads to improved gene expression estimates as well as to the generation of exon counts that allow disambiguating reads between overlapping exons. Unlike other methods that quantify skipped introns, EQP offers a novel way to compute junction counts based on the agreement of the read alignments with the exons on both sides of the junction, thus providing a uniformly derived set of counts. We evaluated the performance of EQP on both simulated and real Illumina RNA-seq data and compared it with other quantification tools. Our results suggest that EQP provides superior gene expression estimates and we illustrate the advantages of EQP's exon and junction counts. The provision of uniformly derived high-quality counts makes EQP an ideal quantification tool for differential expression and differential splicing studies. EQP is freely available for download at https://github.com/Novartis/EQP-cluster .

Description: We describe Boiler, a new software tool for compressing and querying large collections of RNA-seq alignments. Boiler discards most per-read data, keeping only a genomic coverage vector plus a few empirical distributions summarizing the alignments. Since most per-read data is discarded, storage footprint is often much smaller than that achieved by other compression tools. Despite this, the most relevant per-read data can be recovered; we show that Boiler compression has only a slight negative impact on results given by downstream tools for isoform assembly and quantification. Boiler also allows the user to pose fast and useful queries without decompressing the entire file. Boiler is free open source software available from github.com/jpritt/boiler .

Description: Annotation of herpesvirus genomes has traditionally been undertaken through the detection of open reading frames and other genomic motifs, supplemented with sequencing of individual cDNAs. Second generation sequencing and high-density microarray studies have revealed vastly greater herpesvirus transcriptome complexity than is captured by existing annotation. The pervasive nature of overlapping transcription throughout herpesvirus genomes, however, poses substantial problems in resolving transcript structures using these methods alone. We present an approach that combines the unique attributes of Pacific Biosciences Iso-Seq long-read, Illumina short-read and deepCAGE (Cap Analysis of Gene Expression) sequencing to globally resolve polyadenylated isoform structures in replicating Epstein-Barr virus (EBV). Our method, Transcriptome Resolution through Integration of Multi-platform Data (TRIMD), identifies nearly 300 novel EBV transcripts, quadrupling the size of the annotated viral transcriptome. These findings illustrate an array of mechanisms through which EBV achieves functional diversity in its relatively small, compact genome including programmed alternative splicing (e.g. across the IR1 repeats), alternative promoter usage by LMP2 and other latency-associated transcripts, intergenic splicing at the BZLF2 locus, and antisense transcription and pervasive readthrough transcription throughout the genome.

Description: Use of low resolution single cell DNA FISH and population based high resolution chromosome conformation capture techniques have highlighted the importance of pairwise chromatin interactions in gene regulation. However, it is unlikely that associations involving regulatory elements act in isolation of other interacting partners that also influence their impact. Indeed, the influence of multi-loci interactions remains something of an enigma as beyond low-resolution DNA FISH we do not have the appropriate tools to analyze these. Here we present a method that uses standard 4C-seq data to identify multi-loci interactions from the same cell. We demonstrate the feasibility of our method using 4C-seq data sets that identify known pairwise and novel tri-loci interactions involving the Tcrb and Igk antigen receptor enhancers. We further show that the three Igk enhancers, MiE, 3'E and Ed, interact simultaneously in this super-enhancer cluster, which add to our previous findings showing that loss of one element decreases interactions between all three elements as well as reducing their transcriptional output. These findings underscore the functional importance of simultaneous interactions and provide new insight into the relationship between enhancer elements. Our method opens the door for studying multi-loci interactions and their impact on gene regulation in other biological settings.

Description: Module identification is a frequently used approach for mining local structures with more significance in global networks. Recently, a wide variety of bilayer networks are emerging to characterize the more complex biological processes. In the light of special topological properties of bilayer networks and the accompanying challenges, there is yet no effective method aiming at bilayer module identification to probe the modular organizations from the more inspiring bilayer networks. To this end, we proposed the pseudo-3D clustering algorithm, which starts from extracting initial non-hierarchically organized modules and then iteratively deciphers the hierarchical organization of modules according to a bottom-up strategy. Specifically, a modularity function for bilayer modules was proposed to facilitate the algorithm reporting the optimal partition that gives the most accurate characterization of the bilayer network. Simulation studies demonstrated its robustness and outperformance against alternative competing methods. Specific applications to both the soybean and human miRNA-gene bilayer networks demonstrated that the pseudo-3D clustering algorithm successfully identified the overlapping, hierarchically organized and highly cohesive bilayer modules. The analyses on topology, functional and human disease enrichment and the bilayer subnetwork involved in soybean fat biosynthesis provided both the theoretical and biological evidence supporting the effectiveness and robustness of pseudo-3D clustering algorithm.

Description: Gene-order-based comparison of multiple genomes provides signals for functional analysis of genes and the evolutionary process of genome organization. Gene clusters are regions of co-localized genes on genomes of different species. The rapid increase in sequenced genomes necessitates bioinformatics tools for finding gene clusters in hundreds of genomes. Existing tools are often restricted to few (in many cases, only two) genomes, and often make restrictive assumptions such as short perfect conservation, conserved gene order or monophyletic gene clusters. We present Gecko 3, an open-source software for finding gene clusters in hundreds of bacterial genomes, that comes with an easy-to-use graphical user interface. The underlying gene cluster model is intuitive, can cope with low degrees of conservation as well as misannotations and is complemented by a sound statistical evaluation. To evaluate the biological benefit of Gecko 3 and to exemplify our method, we search for gene clusters in a dataset of 678 bacterial genomes using Synechocystis sp. PCC 6803 as a reference. We confirm detected gene clusters reviewing the literature and comparing them to a database of operons; we detect two novel clusters, which were confirmed by publicly available experimental RNA-Seq data. The computational analysis is carried out on a laptop computer in 〈40 min.

Description: Surface nuclear magnetic resonance (NMR) is a unique geophysical method due to its direct sensitivity to water. A key limitation to overcome is the difficulty of making surface NMR measurements in environments with anthropogenic electromagnetic noise, particularly constant frequency sources such as powerlines. Here we present a method of removing harmonic noise by utilizing frequency domain symmetry of surface NMR signals to reconstruct portions of the spectrum corrupted by frequency-domain noise peaks. This method supplements the existing NMR processing workflow and is applicable after despiking, coherent noise cancellation, and stacking. The symmetry based correction is simple, grounded in mathematical theory describing NMR signals, does not introduce errors into the data set, and requires no prior knowledge about the harmonics. Modelling and field examples show that symmetry based noise removal reduces the effects of harmonics. In one modelling example, symmetry based noise removal improved signal-to-noise ratio in the data by 10 per cent. This improvement had noticeable effects on inversion parameters including water content and the decay constant T 2 *. Within water content profiles, aquifer boundaries and water content are more accurate after harmonics are removed. Fewer spurious water content spikes appear within aquifers, which is especially useful for resolving multilayered structures. Within T 2 * profiles, estimates are more accurate after harmonics are removed, especially in the lower half of profiles.

Description: In this work, we study seismoelectric conversions generated in the vadose zone, when this region is traversed by a pure SH wave. We assume that the soil is a 1-D partially saturated lossy porous medium and we use the van Genuchten's constitutive model to describe the water saturation profile. Correspondingly, we extend Pride's formulation to deal with partially saturated media. In order to evaluate the influence of different soil textures we perform a numerical analysis considering, among other relevant properties, the electrokinetic coupling, coseismic responses and interface responses (IRs). We propose new analytical transfer functions for the electric and magnetic field as a function of the water saturation, modifying those of Bordes et al. and Garambois & Dietrich, respectively. Further, we introduce two substantially different saturation-dependent functions into the electrokinetic (EK) coupling linking the poroelastic and the electromagnetic wave equations. The numerical results show that the electric field IRs markedly depend on the soil texture and the chosen EK coupling model, and are several orders of magnitude stronger than the electric field coseismic ones. We also found that the IRs of the water table for the silty and clayey soils are stronger than those for the sandy soils, assuming a non-monotonous saturation dependence of the EK coupling, which takes into account the charged air–water interface. These IRs have been interpreted as the result of the jump in the viscous electric current density at the water table. The amplitude of the IR is obtained using a plane SH wave, neglecting both the spherical spreading and the restriction of its origin to the first Fresnel zone, effects that could lower the predicted values. However, we made an estimation of the expected electric field IR amplitudes detectable in the field by means of the analytical transfer functions, accounting for spherical spreading of the SH seismic waves. This prediction yields a value of 15 μV m –1 , which is compatible with reported values.

Description: In recent years, marine controlled source electromagnetics (CSEM) has found increasing use in hydrocarbon exploration due to its ability to detect thin resistive zones beneath the seafloor. It is the purpose of this paper to evaluate the physics of CSEM for an ocean whose electrical thickness is comparable to or much thinner than that of the overburden using the in-line configuration through examination of the elliptically polarized seafloor electric field, the time-averaged energy flow depicted by the real part of the complex Poynting vector, energy dissipation through Joule heating and the Fréchet derivatives of the seafloor field with respect to the subseafloor conductivity that is assumed to be isotropic. The deep water (ocean layer electrically much thicker than the overburden) seafloor EM response for a model containing a resistive reservoir layer has a greater amplitude and reduced phase as a function of offset compared to that for a half-space, or a stronger and faster response. For an ocean whose electrical thickness is comparable to or much smaller than that of the overburden, the electric field displays a greater amplitude and reduced phase at small offsets, shifting to a stronger amplitude and increased phase at intermediate offsets and a weaker amplitude and enhanced phase at long offsets, or a stronger and faster response that first changes to stronger and slower, and then transitions to weaker and slower. These transitions can be understood by visualizing the energy flow throughout the structure caused by the competing influences of the dipole source and guided energy flow in the reservoir layer, and the air interaction caused by coupling of the entire subseafloor resistivity structure with the sea surface. A stronger and faster response occurs when guided energy flow is dominant, while a weaker and slower response occurs when the air interaction is dominant. However, at intermediate offsets for some models, the air interaction can partially or fully reverse the direction of energy flux in the reservoir layer toward rather than away from the source, resulting in a stronger and slower response. The Fréchet derivatives are dominated by preferential sensitivity to the reservoir layer conductivity for all water depths except at high frequencies, but also display a shift with offset from the galvanic to the inductive mode in the underburden and overburden due to the interplay of guided energy flow and the air interaction. This means that the sensitivity to the horizontal conductivity is almost as strong as to the vertical component in the shallow parts of the subsurface, and in fact is stronger than the vertical sensitivity deeper down. However, the sensitivity to horizontal conductivity is still weak compared to the vertical component within thin resistive regions. The horizontal sensitivity is gradually decreased when the water becomes deep. These observations in part explain the success of shallow towed CSEM using only measurements of the in-line component of the electric field.

Description: Joint inversion and time-lapse inversion techniques of geophysical data are often implemented in an attempt to improve imaging of complex subsurface structures and dynamic processes by minimizing negative effects of random and uncorrelated spatial and temporal noise in the data. We focus on the structural cross-gradient (SCG) approach (enforcing recovered models to exhibit similar spatial structures) in combination with time-lapse inversion constraints applied to surface-based electrical resistivity and seismic traveltime refraction data. The combination of both techniques is justified by the underlying petrophysical models. We investigate the benefits and trade-offs of SCG and time-lapse constraints. Using a synthetic case study, we show that a combined joint time-lapse inversion approach provides an overall improvement in final recovered models. Additionally, we introduce a new approach to reweighting SCG constraints based on an iteratively updated normalized ratio of model sensitivity distributions at each time-step. We refer to the new technique as the Automatic Joint Constraints (AJC) approach. The relevance of the new joint time-lapse inversion process is demonstrated on the synthetic example. Then, these approaches are applied to real time-lapse monitoring field data collected during a quarter-scale earthen embankment induced-piping failure test. The use of time-lapse joint inversion is justified by the fact that a change of porosity drives concomitant changes in seismic velocities (through its effect on the bulk and shear moduli) and resistivities (through its influence upon the formation factor). Combined with the definition of attributes (i.e. specific characteristics) of the evolving target associated with piping, our approach allows localizing the position of the preferential flow path associated with internal erosion. This is not the case using other approaches.

Description: Geophysical inversion should ideally produce geologically realistic subsurface models that explain the available data. Multiple-point statistics is a geostatistical approach to construct subsurface models that are consistent with site-specific data, but also display the same type of patterns as those found in a training image. The training image can be seen as a conceptual model of the subsurface and is used as a non-parametric model of spatial variability. Inversion based on multiple-point statistics is challenging due to high nonlinearity and time-consuming geostatistical resimulation steps that are needed to create new model proposals. We propose an entirely new model proposal mechanism for geophysical inversion that is inspired by texture synthesis in computer vision. Instead of resimulating pixels based on higher-order patterns in the training image, we identify a suitable patch of the training image that replace a corresponding patch in the current model without breaking the patterns found in the training image, that is, remaining consistent with the given prior. We consider three cross-hole ground-penetrating radar examples in which the new model proposal mechanism is employed within an extended Metropolis Markov chain Monte Carlo (MCMC) inversion. The model proposal step is about 40 times faster than state-of-the-art multiple-point statistics resimulation techniques, the number of necessary MCMC steps is lower and the quality of the final model realizations is of similar quality. The model proposal mechanism is presently limited to 2-D fields, but the method is general and can be applied to a wide range of subsurface settings and geophysical data types.

Description: De-novo motif search is a frequently applied bioinformatics procedure to identify and prioritize recurrent elements in sequences sets for biological investigation, such as the ones derived from high-throughput differential expression experiments. Several algorithms have been developed to perform motif search, employing widely different approaches and often giving divergent results. In order to maximize the power of these investigations and ultimately be able to draft solid biological hypotheses, there is the need for applying multiple tools on the same sequences and merge the obtained results. However, motif reporting formats and statistical evaluation methods currently make such an integration task difficult to perform and mostly restricted to specific scenarios. We thus introduce here the Dynamic Motif Integration Toolkit (DynaMIT), an extremely flexible platform allowing to identify motifs employing multiple algorithms, integrate them by means of a user-selected strategy and visualize results in several ways; furthermore, the platform is user-extendible in all its aspects. DynaMIT is freely available at http://cibioltg.bitbucket.org .

Description: The comprehensive multiplatform genomics data generated by The Cancer Genome Atlas (TCGA) Research Network is an enabling resource for cancer research. It includes an unprecedented amount of microRNA sequence data: ~11 000 libraries across 33 cancer types. Combined with initiatives like the National Cancer Institute Genomics Cloud Pilots, such data resources will make intensive analysis of large-scale cancer genomics data widely accessible. To support such initiatives, and to enable comparison of TCGA microRNA data to data from other projects, we describe the process that we developed and used to generate the microRNA sequence data, from library construction through to submission of data to repositories. In the context of this process, we describe the computational pipeline that we used to characterize microRNA expression across large patient cohorts.

Description: DNA methylation differences capture substantial information about the molecular and gene-regulatory states among biological subtypes. Enrichment-based next generation sequencing methods such as MBD-isolated genome sequencing (MiGS) and MeDIP-seq are appealing for studying DNA methylation genome-wide in order to distinguish between biological subtypes. However, current analytic tools do not provide optimal features for analyzing three-group or larger study designs. MethylAction addresses this need by detecting all possible patterns of statistically significant hyper- and hypo- methylation in comparisons involving any number of groups. Crucially, significance is established at the level of differentially methylated regions (DMRs), and bootstrapping determines false discovery rates (FDRs) associated with each pattern. We demonstrate this functionality in a four-group comparison among benign prostate and three clinical subtypes of prostate cancer and show that the bootstrap FDRs are highly useful in selecting the most robust patterns of DMRs. Compared to existing tools that are limited to two-group comparisons, MethylAction detects more DMRs with strong differential methylation measurements confirmed by whole genome bisulfite sequencing and offers a better balance between precision and recall in cross-cohort comparisons. MethylAction is available as an R package at http://jeffbhasin.github.io/methylaction .

Description: The advanced medium-throughput NanoString nCounter technology has been increasingly used for mRNA or miRNA differential expression (DE) studies due to its advantages including direct measurement of molecule expression levels without amplification, digital readout and superior applicability to formalin fixed paraffin embedded samples. However, the analysis of nCounter data is hampered because most methods developed are based on t-tests, which do not fit the count data generated by the NanoString nCounter system. Furthermore, data normalization procedures of current methods are either not suitable for counts or not specific for NanoString nCounter data. We develop a novel DE detection method based on NanoString nCounter data. The method, named NanoStringDiff, considers a generalized linear model of the negative binomial family to characterize count data and allows for multifactor design. Data normalization is incorporated in the model framework through data normalization parameters, which are estimated from positive controls, negative controls and housekeeping genes embedded in the nCounter system. We propose an empirical Bayes shrinkage approach to estimate the dispersion parameter in the model and a likelihood ratio test to identify differentially expressed genes. Simulations and real data analysis demonstrate that the proposed method performs better than existing methods.

Description: Electromagnetic responses reflect the interaction between applied electromagnetic fields and heterogeneous geoelectrical structures. Quantifying the relationship between multiscale electrical properties and the observed electromagnetic response is therefore important for meaningful geologic interpretation. We present here examples of near-surface electromagnetic responses whose spatial fluctuations appear on all length scales, are repeatable and fractally distributed, supporting the notion of a ‘rough geology’ exhibiting multiscale hierarchical structure. Bounded by end member cases from homogenized isotropic and anisotropic media, we present numerical modelling results of the electromagnetic responses of textured and spatially correlated, stochastic geologic media, demonstrating that the electromagnetic response is a power law distribution, rather than a smooth response polluted with random, incoherent noise as commonly assumed. Our modelling results show that these electromagnetic responses due to spatially correlated geologic textures are examples of fractional Brownian motion. Furthermore, our results suggest that the fractal behaviour of the electromagnetic responses is correlated with degree of the spatial correlation, the contrasts in ground conductivity, and the preferred orientation of small-scale heterogeneity. In addition, the EM responses acquired across a fault zone comprising different lithological units and varying wavelengths of geologic heterogeneity also support our inferences from numerical modelling.

Description: We introduce RNA2DNAlign, a computational framework for quantitative assessment of allele counts across paired RNA and DNA sequencing datasets. RNA2DNAlign is based on quantitation of the relative abundance of variant and reference read counts, followed by binomial tests for genotype and allelic status at SNV positions between compatible sequences. RNA2DNAlign detects positions with differential allele distribution, suggesting asymmetries due to regulatory/structural events. Based on the type of asymmetry, RNA2DNAlign outlines positions likely to be implicated in RNA editing, allele-specific expression or loss, somatic mutagenesis or loss-of-heterozygosity (the first three also in a tumor-specific setting). We applied RNA2DNAlign on 360 matching normal and tumor exomes and transcriptomes from 90 breast cancer patients from TCGA. Under high-confidence settings, RNA2DNAlign identified 2038 distinct SNV sites associated with one of the aforementioned asymetries, the majority of which have not been linked to functionality before. The performance assessment shows very high specificity and sensitivity, due to the corroboration of signals across multiple matching datasets. RNA2DNAlign is freely available from http://github.com/HorvathLab/NGS as a self-contained binary package for 64-bit Linux systems.

Description: The oceanic lithosphere in the Bay of Bengal (BOB) formed 80–120 Ma following the breakup of eastern Gondwanaland. Since its formation, it has been affected by the emplacement of two long N-S trending linear aseismic ridges (85°E and Ninetyeast) and by the loading of ca . 20-km of sediments of the Bengal Fan. Here, we present the results of a combined spatial and spectral domain analysis of residual geoid, bathymetry and gravity data constrained by seismic reflection and refraction data. Self-consistent geoid and gravity modelling defined by temperature-dependent mantle densities along a N–S transect in the BOB region revealed that the depth to the lithosphere–asthenosphere boundary (LAB) deepens steeply from 77 km in the south to 127 km in north, with the greater thickness being anomalously thick compared to the lithosphere of similar-age beneath the Pacific Ocean. The Geoid-Topography Ratio (GTR) analysis of the 85°E and Ninetyeast ridges indicate that they are compensated at shallow depths. Effective elastic thickness ( T e ) estimates obtained through admittance/ coherence analysis as well as the flexural modelling along these ridges led to the conclusions: (i) 85°E Ridge was emplaced in off-ridge environment ( T e  = 10–15 km); (ii) the higher T e values of ~25 km over the Afanasy Nikitin Seamount (ANS) reflect the secondary emplacement of the seamount peaks in off-ridge environment, (iii) that the emplacement of the Ninetyeast Ridge north of 2°N occurred in an off-ridge environment as indicated by higher T e values (25–30 km). Furthermore, the admittance analysis of geoid and bathymetry revealed that the admittance signatures at wavelengths 〉800 km are compensated by processes related to upper mantle convection.