ALBERT

Description: 3-D electromagnetic (EM) studies of the Earth have advanced significantly over the past decade. Despite a certain success of the 3-D EM inversions of real data sets, the quantitative assessment of the recovered models is still a challenging problem. It is known that one can gain valuable information about model uncertainties from the analysis of Hessian matrix. However, even with modern computational capabilities the calculation of the Hessian matrix based on numerical differentiation is extremely time consuming. Much more efficient way to compute the Hessian matrix is provided by an ‘adjoint sources’ methodology. The computation of Hessian matrix (and Hessian-vector products) using adjoint formulation is now well-established approach, especially in seismic inverse modelling. As for EM inverse modelling we did not find in the literature a description of the approach, which would allow EM researchers to apply this methodology in a straightforward manner to their scenario of interest. In the paper, we present formalism for the efficient calculation of the Hessian matrix using adjoint sources approach. We also show how this technique can be implemented to calculate multiple Hessian-vector products very efficiently. The formalism is general in the sense that it allows to work with responses that arise in EM problem set-ups either with natural- or controlled-source excitations. The formalism allows for various types of parametrization of the 3-D conductivity distribution. Using this methodology one can readily obtain appropriate formulae for the specific sounding methods. To illustrate the concept we provide such formulae for two EM techniques: magnetotellurics and controlled-source sounding with vertical magnetic dipole as a source.

Description: With advancing computational resources, 3-D inversion techniques have become feasible in recent years and are now a more widely used tool for magnetotelluric (MT) data interpretation. Galvanic distortion caused by small-scale near-surface inhomogeneities remains an obstacle for 3-D MT inversion which so far has experienced little attention. If not considered properly, the effect on 3-D inversion can be immense and result in erroneous subsurface models and interpretations. To tackle the problem we implemented inversion of the distortion-free phase tensor into the ModEM inversion package. The dimensionless phase tensor components describe only variations of the conductivity structure. When inverting these data, particular care has to be taken of the conductivity structure in the a priori model, which provides the reference frame when transferring the information from phase tensors into absolute conductivity values. Our results obtained with synthetic data show that phase tensor inversion can recover the regional conductivity structure in presence of galvanic distortion if the a priori model provides a reasonable assumption for the regional resistivity average. Joint inversion of phase tensor data and vertical magnetic transfer functions improves recovery of the absolute resistivity structure and is less dependent on the prior model. We also used phase tensor inversion for a data set of more than 250 MT sites from the central San Andreas fault, California, where a number of sites showed significant galvanic distortion. We find the regional structure of the phase tensor inversion results compatible with previously obtained models from impedance inversion. In the vicinity of distorted sites, phase tensor inversion models exhibit more homogeneous/smoother conductivity structures.

Description: Analysis of more than 10 yr of vertical magnetic transfer function (VTF) estimates obtained at 12 mid-latitude sites, located in different continents and tectonic settings, reveals significant temporal variations for a period range between approximately 250 and 2000 s. The most ubiquitous pattern is a seasonal modulation of the VTF element that relates the vertical to the horizontal north–south magnetic components ( Tx ), which shows a high peak around the June solstice (and a low peak around the December solstice) regardless of the location of the site. To quantify the influence of this source effect on the amplitude of VTFs, we modelled the temporal variations of VTFs using a function with dependence on season and magnetic activity indexes. The model shows that differences between VTF estimates obtained at seasonal peaks can reach 0.08 of Tx absolute values and that the effect increases with latitude and period. Seasonal variations are observed also in the VTF component relating vertical to horizontal east–west magnetic components ( Ty ), but here the pattern with respect to the geographic distribution is less clear. In addition to seasonal trends, we observe long-term modulations correlating with the 11-yr solar cycle at some sites. The influence of these external source effects should be taken into account, before attempting a geological interpretation of the VTFs. It can be misleading, for example, to combine or compare VTFs obtained from long-period geomagnetic data acquired at different seasons or years. An effective method to estimate and remove these source effects from VTFs is by comparison with temporal variations of VTFs from synchronously recorded data at sites located at similar latitude (〈5° of difference) and longitude (〈10° of difference). Source effects in temporal variations of VTFs can be identified as those patterns that exhibit similar amplitudes and significant correlation with the geomagnetic activity at all compared sites. We also provide a second-order polynomial which can be used to estimate the amplitude of the seasonal variations in the Tx component globally as a function of latitude.

Description: ChIP-seq is increasingly used to characterize transcription factor binding and chromatin marks at a genomic scale. Various tools are now available to extract binding motifs from peak data sets. However, most approaches are only available as command-line programs, or via a website but with size restrictions. We present peak-motifs , a computational pipeline that discovers motifs in peak sequences, compares them with databases, exports putative binding sites for visualization in the UCSC genome browser and generates an extensive report suited for both naive and expert users. It relies on time- and memory-efficient algorithms enabling the treatment of several thousand peaks within minutes. Regarding time efficiency, peak-motifs outperforms all comparable tools by several orders of magnitude. We demonstrate its accuracy by analyzing data sets ranging from 4000 to 1 28 000 peaks for 12 embryonic stem cell-specific transcription factors. In all cases, the program finds the expected motifs and returns additional motifs potentially bound by cofactors. We further apply peak-motifs to discover tissue-specific motifs in peak collections for the p300 transcriptional co-activator. To our knowledge, peak-motifs is the only tool that performs a complete motif analysis and offers a user-friendly web interface without any restriction on sequence size or number of peaks.

Description: Deep transcriptome sequencing (RNA-Seq) has become a vital tool for studying the state of cells in the context of varying environments, genotypes and other factors. RNA-Seq profiling data enable identification of novel isoforms, quantification of known isoforms and detection of changes in transcriptional or RNA-processing activity. Existing approaches to detect differential isoform abundance between samples either require a complete isoform annotation or fall short in providing statistically robust and calibrated significance estimates. Here, we propose a suite of statistical tests to address these open needs: a parametric test that uses known isoform annotations to detect changes in relative isoform abundance and a non-parametric test that detects differential read coverages and can be applied when isoform annotations are not available. Both methods account for the discrete nature of read counts and the inherent biological variability. We demonstrate that these tests compare favorably to previous methods, both in terms of accuracy and statistical calibrations. We use these techniques to analyze RNA-Seq libraries from Arabidopsis thaliana and Drosophila melanogaster. The identified differential RNA processing events were consistent with RT–qPCR measurements and previous studies. The proposed toolkit is available from http://bioweb.me/rdiff and enables in-depth analyses of transcriptomes, with or without available isoform annotation.

Description: A computational method is given for solving the forward modelling problem for transient electromagnetic exploration. Its key features are the discretization of the quasi-static Maxwell's equations in space using the first-kind family of curl-conforming Nédélec elements combined with time integration using rational Krylov methods. We show how rational Krylov methods can also be used to solve the same problem in the frequency domain followed by a synthesis of the transient solution using the fast Hankel transform, and we argue that the pure time-domain solution is more efficient. We also propose a new surrogate optimization approach for selecting the pole parameters of the rational Krylov method which leads to convergence within an a priori determined number of iterations independent of mesh size and conductivity structure. These poles are repeated in a cyclic fashion, which, in combination with direct solvers for the discrete problem, results in significantly faster solution times than previously proposed schemes.

Description: Previous magnetotelluric (MT) studies of the high-temperature Coso geothermal system in California identified a subvertical feature of low resistivity (2–5 Ohm m) and appreciable lateral extent (〉1 km) in the producing zone of the East Flank field. However, these models could not reproduce gross 3-D effects in the recorded data. We perform 3-D full-tensor inversion and retrieve a resistivity model that out-performs previous 2-D and 3-D off-diagonal models in terms of its fit to the complete 3-D MT data set as well as the degree of modelling bias. Inclusion of secondary Z xx and Z yy data components leads to a robust east-dip (60) to the previously identified conductive East Flank reservoir feature, which correlates strongly with recently mapped surface faults, downhole well temperatures, 3-D seismic reflection data, and local microseismicity. We perform synthetic forward modelling to test the best-fit dip of this conductor using the response at a nearby MT station. We interpret the dipping conductor as a fractured and fluidized compartment, which is structurally controlled by an unmapped blind East Flank fault zone.