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  • Journals
  • Articles  (28)
  • Latest Papers from Table of Contents or Articles in Press  (28)
  • Computational Methods  (14)
  • Polymorphism/mutation detection  (10)
  • RNA characterisation and manipulation
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  • 2015-2019  (28)
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  • Latest Papers from Table of Contents or Articles in Press  (28)
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  • Biology  (28)
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  • 1
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    SPATIAL: A System-level PAThway Impact AnaLysis approach (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-21
    Description: The goal of pathway analysis is to identify the pathways that are significantly impacted when a biological system is perturbed, e.g. by a disease or drug. Current methods treat pathways as independent entities. However, many signals are constantly sent from one pathway to another, essentially linking all pathways into a global, system-wide complex. In this work, we propose a set of three pathway analysis methods based on the impact analysis, that performs a system-level analysis by considering all signals between pathways, as well as their overlaps. Briefly, the global system is modeled in two ways: (i) considering the inter-pathway interaction exchange for each individual pathways, and (ii) combining all individual pathways to form a global, system-wide graph. The third analysis method is a hybrid of these two models. The new methods were compared with DAVID, GSEA, GSA, PathNet, Crosstalk and SPIA on 23 GEO data sets involving 19 tissues investigated in 12 conditions. The results show that both the ranking and the P -values of the target pathways are substantially improved when the analysis considers the system-wide dependencies and interactions between pathways.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 2
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    VarDict: a novel and versatile variant caller for next-generation sequencing in cancer research (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-21
    Description: Accurate variant calling in next generation sequencing (NGS) is critical to understand cancer genomes better. Here we present VarDict, a novel and versatile variant caller for both DNA- and RNA-sequencing data. VarDict simultaneously calls SNV, MNV, InDels, complex and structural variants, expanding the detected genetic driver landscape of tumors. It performs local realignments on the fly for more accurate allele frequency estimation. VarDict performance scales linearly to sequencing depth, enabling ultra-deep sequencing used to explore tumor evolution or detect tumor DNA circulating in blood. In addition, VarDict performs amplicon aware variant calling for polymerase chain reaction (PCR)-based targeted sequencing often used in diagnostic settings, and is able to detect PCR artifacts. Finally, VarDict also detects differences in somatic and loss of heterozygosity variants between paired samples. VarDict reprocessing of The Cancer Genome Atlas (TCGA) Lung Adenocarcinoma dataset called known driver mutations in KRAS, EGFR, BRAF, PIK3CA and MET in 16% more patients than previously published variant calls. We believe VarDict will greatly facilitate application of NGS in clinical cancer research.
    Keywords: Polymorphism/mutation detection
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 3
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    Molecularly resolved label-free sensing of single nucleobase mismatches by interfacial LNA probes (2016)
    Oxford University Press
    Details
    Publication Date: 2016-05-06
    Description: So far, there has been no report on molecularly resolved discrimination of single nucleobase mismatches using surface-confined single stranded locked nucleic acid (ssLNA) probes. Herein, it is exemplified using a label-independent force-sensing approach that an optimal coverage of 12-mer ssLNA sensor probes formed onto gold(111) surface allows recognition of ssDNA targets with twice stronger force sensitivity than 12-mer ssDNA sensor probes. The force distributions are reproducible and the molecule-by-molecule force measurements are largely in agreement with ensemble on-surface melting temperature data. Importantly, the molecularly resolved detection is responsive to the presence of single nucleobase mismatches in target sequences. Since the labelling steps can be eliminated from protocol, and each force-based detection event occurs within milliseconds' time scale, the force-sensing assay is potentially capable of rapid detection. The LNA probe performance is indicative of versatility in terms of substrate choice - be it gold (for basic research and array-based applications) or silicon (for ‘lab-on-a-chip’ type devices). The nucleic acid microarray technologies could therefore be generally benefited by adopting the LNA films, in place of DNA. Since LNA is nuclease-resistant, unlike DNA, and the LNA-based assay is sensitive to single nucleobase mismatches, the possibilities for label-free in vitro rapid diagnostics based on the LNA probes may be explored.
    Keywords: Polymorphism/mutation detection
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 4
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    A fast and powerful W-test for pairwise epistasis testing (2016)
    Oxford University Press
    Details
    Publication Date: 2016-07-09
    Description: Epistasis plays an essential role in the development of complex diseases. Interaction methods face common challenge of seeking a balance between persistent power, model complexity, computation efficiency, and validity of identified bio-markers. We introduce a novel W-test to identify pairwise epistasis effect, which measures the distributional difference between cases and controls through a combined log odds ratio. The test is model-free, fast, and inherits a Chi-squared distribution with data adaptive degrees of freedom. No permutation is needed to obtain the P -values. Simulation studies demonstrated that the W-test is more powerful in low frequency variants environment than alternative methods, which are the Chi-squared test, logistic regression and multifactor-dimensionality reduction (MDR). In two independent real bipolar disorder genome-wide associations (GWAS) datasets, the W-test identified significant interactions pairs that can be replicated, including SLIT3-CENPN, SLIT3-TMEM132D, CNTNAP2-NDST4 and CNTCAP2-RTN4R . The genes in the pairs play central roles in neurotransmission and synapse formation. A majority of the identified loci are undiscoverable by main effect and are low frequency variants. The proposed method offers a powerful alternative tool for mapping the genetic puzzle underlying complex disorders.
    Keywords: Polymorphism/mutation detection
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 5
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    Goldmine integrates information placing genomic ranges into meaningful biological contexts (2016)
    Oxford University Press
    Details
    Publication Date: 2016-07-09
    Description: Bioinformatic analysis often produces large sets of genomic ranges that can be difficult to interpret in the absence of genomic context. Goldmine annotates genomic ranges from any source with gene model and feature contexts to facilitate global descriptions and candidate loci discovery. We demonstrate the value of genomic context by using Goldmine to elucidate context dynamics in transcription factor binding and to reveal differentially methylated regions (DMRs) with context-specific functional correlations. The open source R package and documentation for Goldmine are available at http://jeffbhasin.github.io/goldmine .
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 6
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    Defining the multivalent functions of CTCF from chromatin state and three-dimensional chromatin interactions (2016)
    Oxford University Press
    Details
    Publication Date: 2016-07-28
    Description: CCCTC-binding factor (CTCF) is a multi-functional protein that is assigned various, even contradictory roles in the genome. High-throughput sequencing-based technologies such as ChIP-seq and Hi-C provided us the opportunity to assess the multivalent functions of CTCF in the human genome. The location of CTCF-binding sites with respect to genomic features provides insights into the possible roles of this protein. Here we present the first genome-wide survey and characterization of three important functions of CTCF: enhancer insulator, chromatin barrier and enhancer linker. We developed a novel computational framework to discover the multivalent functions of CTCF based on chromatin state and three-dimensional chromatin architecture. We applied our method to five human cell lines and identified ~46 000 non-redundant CTCF sites related to the three functions. Disparate effects of these functions on gene expression were found and distinct genomic features of these CTCF sites were characterized in GM12878 cells. Finally, we investigated the cell-type specificities of CTCF sites related to these functions across five cell types. Our study provides new insights into the multivalent functions of CTCF in the human genome.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 7
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    Robust classification of protein variation using structural modelling and large-scale data integration (2016)
    Oxford University Press
    Details
    Publication Date: 2016-04-08
    Description: Existing methods for interpreting protein variation focus on annotating mutation pathogenicity rather than detailed interpretation of variant deleteriousness and frequently use only sequence-based or structure-based information. We present VIPUR, a computational framework that seamlessly integrates sequence analysis and structural modelling (using the Rosetta protein modelling suite) to identify and interpret deleterious protein variants. To train VIPUR, we collected 9477 protein variants with known effects on protein function from multiple organisms and curated structural models for each variant from crystal structures and homology models. VIPUR can be applied to mutations in any organism's proteome with improved generalized accuracy (AUROC .83) and interpretability (AUPR .87) compared to other methods. We demonstrate that VIPUR's predictions of deleteriousness match the biological phenotypes in ClinVar and provide a clear ranking of prediction confidence. We use VIPUR to interpret known mutations associated with inflammation and diabetes, demonstrating the structural diversity of disrupted functional sites and improved interpretation of mutations associated with human diseases. Lastly, we demonstrate VIPUR's ability to highlight candidate variants associated with human diseases by applying VIPUR to de novo variants associated with autism spectrum disorders.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 8
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    NetDecoder: a network biology platform that decodes context-specific biological networks and gene activities (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-03
    Description: The sequential chain of interactions altering the binary state of a biomolecule represents the ‘information flow’ within a cellular network that determines phenotypic properties. Given the lack of computational tools to dissect context-dependent networks and gene activities, we developed NetDecoder, a network biology platform that models context-dependent information flows using pairwise phenotypic comparative analyses of protein–protein interactions. Using breast cancer, dyslipidemia and Alzheimer's disease as case studies, we demonstrate NetDecoder dissects subnetworks to identify key players significantly impacting cell behaviour specific to a given disease context. We further show genes residing in disease-specific subnetworks are enriched in disease-related signalling pathways and information flow profiles, which drive the resulting disease phenotypes. We also devise a novel scoring scheme to quantify key genes—network routers, which influence many genes, key targets, which are influenced by many genes, and high impact genes, which experience a significant change in regulation. We show the robustness of our results against parameter changes. Our network biology platform includes freely available source code ( http://www.NetDecoder.org ) for researchers to explore genome-wide context-dependent information flow profiles and key genes, given a set of genes of particular interest and transcriptome data. More importantly, NetDecoder will enable researchers to uncover context-dependent drug targets.
    Keywords: Computational Methods
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 9
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    SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features (2016)
    Oxford University Press
    Details
    Publication Date: 2016-06-03
    Description: N 6 -methyladenosine (m 6 A) is a prevalent RNA methylation modification involved in the regulation of degradation, subcellular localization, splicing and local conformation changes of RNA transcripts. High-throughput experiments have demonstrated that only a small fraction of the m 6 A consensus motifs in mammalian transcriptomes are modified. Therefore, accurate identification of RNA m 6 A sites becomes emergently important. For the above purpose, here a computational predictor of mammalian m 6 A site named SRAMP is established. To depict the sequence context around m 6 A sites, SRAMP combines three random forest classifiers that exploit the positional nucleotide sequence pattern, the K-nearest neighbor information and the position-independent nucleotide pair spectrum features, respectively. SRAMP uses either genomic sequences or cDNA sequences as its input. With either kind of input sequence, SRAMP achieves competitive performance in both cross-validation tests and rigorous independent benchmarking tests. Analyses of the informative features and overrepresented rules extracted from the random forest classifiers demonstrate that nucleotide usage preferences at the distal positions, in addition to those at the proximal positions, contribute to the classification. As a public prediction server, SRAMP is freely available at http://www.cuilab.cn/sramp/ .
    Keywords: RNA characterisation and manipulation
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    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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  • 10
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    Ultra-fast local-haplotype variant calling using paired-end DNA-sequencing data reveals somatic mosaicism in tumor and normal blood samples (2016)
    Oxford University Press
    Details
    Publication Date: 2016-02-20
    Description: Somatic mosaicism refers to the existence of somatic mutations in a fraction of somatic cells in a single biological sample. Its importance has mainly been discussed in theory although experimental work has started to emerge linking somatic mosaicism to disease diagnosis. Through novel statistical modeling of paired-end DNA-sequencing data using blood-derived DNA from healthy donors as well as DNA from tumor samples, we present an ultra-fast computational pipeline, LocHap that searches for multiple single nucleotide variants (SNVs) that are scaffolded by the same reads. We refer to scaffolded SNVs as local haplotypes (LH). When an LH exhibits more than two genotypes, we call it a local haplotype variant (LHV). The presence of LHVs is considered evidence of somatic mosaicism because a genetically homogeneous cell population will not harbor LHVs. Applying LocHap to whole-genome and whole-exome sequence data in DNA from normal blood and tumor samples, we find wide-spread LHVs across the genome. Importantly, we find more LHVs in tumor samples than in normal samples, and more in older adults than in younger ones. We confirm the existence of LHVs and somatic mosaicism by validation studies in normal blood samples. LocHap is publicly available at http://www.compgenome.org/lochap .
    Keywords: Polymorphism/mutation detection
    Print ISSN: 0305-1048
    Electronic ISSN: 1362-4962
    Topics: Biology
    Published by Oxford University Press
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