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Generalized random set framework for functional enrichment analysis using primary genomics datasets
2010
Computer applications in the biosciences : CABIOS
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Motivation: Functional enrichment analysis using primary genomics datasets is an emerging approach to complement established methods for functional enrichment based on pre-defined lists of functionally ...
Results: We developed and validated a new statistical framework, Generalized Random Set analysis (GRS), for comparing the genomic signatures in two datasets without the need for gene categorization. ...
ACKNOWLEDGEMENTS Funding: This research was supported by grants from the National Human Genome Research Institute (R01 HG003749), National Library of Medicine (R21 LM009662) and NIEHS Center for Environmental ...
doi:10.1093/bioinformatics/btq593
pmid:20971985
pmcid:PMC3025713
fatcat:7sp3x6y2zzg5hin75wsropfm4a
An integrated ChIP-seq analysis platform with customizable workflows
2011
BMC Bioinformatics
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Conclusions: ChIPseeqer facilitates ChIP-seq data analysis by offering a flexible and powerful set of computational tools that can be used in combination with one another. ...
Results: To address the peak interpretation challenge, we have developed ChIPseeqer, an integrative, comprehensive, fast and user-friendly computational framework for in-depth analysis of ChIP-seq datasets ...
Acknowledgements The authors would like to thank all members of Melnick lab (Weill Cornell Medical College) for their suggestions and ideas during the development of the framework and the Elemento lab ...
doi:10.1186/1471-2105-12-277
pmid:21736739
pmcid:PMC3145611
fatcat:b566plvi35hjhprw3evdqx2gjy
GenomeRunner web server: regulatory similarity and differences define the functional impact of SNP sets
2016
Bioinformatics
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In summary, we show how systematic analysis of genomic data within a regulatory context can help interpreting the functional impact of SNP sets. ...
Besides defining the functional impact of SNP sets, GenomeRunner implements novel regulatory similarity/differential analyses, and cell type-specific regulatory enrichment analysis. ...
In this article, we describe the GenomeRunner web server-an automated framework for the statistical analysis and interpretation of the functional impact of SNP sets using regulatory datasets from the ENCODE ...
doi:10.1093/bioinformatics/btw169
pmid:27153607
pmcid:PMC4965636
fatcat:cqmw7o5cajdrna3bu2jxaqg3p4
Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets
2016
Proceedings of the National Academy of Sciences of the United States of America
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This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets. ...
Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition ...
(F) Enrichment analysis of drug targets using literature-and degree-controlled random sets. Random sets are generated as explained in B. ...
doi:10.1073/pnas.1603992113
pmid:27091990
pmcid:PMC4983807
fatcat:gazf7jgbqjakbimgi27n5wbcpm
Evidence for sequence biases associated with patterns of histone methylation
2012
BMC Genomics
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While various mechanisms have been implicated in establishing and maintaining epigenetic patterns at specific locations in the genome, they are generally believed to be independent of primary DNA sequence ...
mechanisms responsible for global histone modifications may interpret genomic sequence in various ways. ...
Acknowledgements We thank J Zhu for computational resources and discussions, and U Ohler, T Furey, G Crawford and members of the Willard Lab for discussions and comments on the manuscript. ...
doi:10.1186/1471-2164-13-367
pmid:22857523
pmcid:PMC3532361
fatcat:g4o6hrdz2ndh7dldqip5j6xatm
TRIAGE: A web-based iterative analysis platform integrating pathway and network databases optimizes hit selection from high- throughput assays
[article]
2020
bioRxiv
pre-print
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Using a set of three highly studied genome-wide datasets for HIV host factors that have been broadly cited for their limited number of shared candidates, we characterize the specific complementary contributions ...
of commonly used analysis approaches and find an optimal framework by which to integrate these methods. ...
significance and magnitude of the overlap in screen hits by use of the iterative analysis strategy which we name TRIAGE, for Throughput Ranking by Iterative Analysis of Genomic Enrichment. ...
doi:10.1101/2020.07.15.204917
fatcat:x4na2cqcgfgcpdl4ik5nconk3q
Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models
2017
Scientific Reports
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We perform an extensive comparison of Bayesian optimized deep survival models and other state of the art machine learning methods for survival analysis, and describe a framework for interpreting deep survival ...
Translating the vast data generated by genomic platforms into accurate predictions of clinical outcomes is a fundamental challenge in genomic medicine. ...
a performance bias for CEN by generating new randomizations when CEN execution fails. ...
doi:10.1038/s41598-017-11817-6
pmid:28916782
pmcid:PMC5601479
fatcat:jl2ebqohwzdvpbts42lu6s3by4
STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets
2018
Nucleic Acids Research
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The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the ...
For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining ...
We thank Tudor Oprea and the Illuminating the Druggable Genome project for help in improving the text mining, and Daniel Mende and Sofia Forslund for their help in selecting a non-redundant set of high-quality ...
doi:10.1093/nar/gky1131
pmid:30476243
fatcat:l6c2fugi3re7pk7agroo52cqqq
Predicting clinical outcomes from large scale cancer genomic profiles with deep survival models
[article]
2017
bioRxiv
pre-print
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We perform an extensive comparison of Bayesian optimized deep survival models and other state of the art machine learning methods for survival analysis, and describe a framework for interpreting deep survival ...
Translating the vast data generated by genomic platforms into accurate predictions of clinical outcomes is a fundamental challenge in genomic medicine. ...
a performance bias for CEN by generating new randomizations when CEN execution fails. ...
doi:10.1101/131367
fatcat:53vhmj67rvhozmbqmpm57glm4u
Spatial localization of co-regulated genes exceeds genomic gene clustering in the Saccharomyces cerevisiae genome
2013
Nucleic Acids Research
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for the primary gene order. ...
We develop a data-driven method for the interpolation and the embedding of such datasets and introduce statistics that enable the comparison of the spatial and genomic densities of genes. ...
ACKNOWLEDGEMENTS We thank Eitan Yaffe, Israel Steinfeld, Florian Wagner, David Silver, Yael Mandel-Gutfreund, Nir Ailon and Amit Singer for advice and critical readings of the manuscript. ...
doi:10.1093/nar/gks1360
pmid:23303780
pmcid:PMC3575811
fatcat:lrfxbf4lujgvhki2s4aobzy5zi
EpiMINE, a computational program for mining epigenomic data
2016
Epigenetics & Chromatin
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It is a user-friendly, stand-alone computational program designed to support multiple datasets, for performing genome-wide correlative and quantitative analysis of ChIP-seq and RNA-seq data. ...
Conclusions: EpiMINE performs different kinds of genome-wide quantitative and correlative analyses, using ChIPseq-and RNA-seq-related datasets. ...
We acknowledge the ENCODE consortium for generating data from different tissues and cell types and for making them publicly available. ...
doi:10.1186/s13072-016-0095-z
pmid:27708717
pmcid:PMC5043526
fatcat:rmvksp6libbalj2gon5sliypxm
A Streamlined and Generalized Analysis of Chromatin ImmunoPrecipitation Paired-End diTag Data
[chapter]
2008
Lecture Notes in Computer Science
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The algorithms were evaluated using three real-world datasets. Using motif enrichment as indirect evidence and additional ChIP-qPCR validations, the overall performance was consistently satisfactory. ...
The recently developed sequencing-based genome-wide approach ChIP-PET (Chromatin ImmunoPrecipitation coupled with Paired-End diTag analysis) permits accurate and unbiased mapping of TF-DNA interactions ...
We would like to thank Jane Thomsen for providing the ChIP-qPCR validation data of the ER library. ...
doi:10.1007/978-3-540-69389-5_16
fatcat:jpi6at37nvc3fhocmyt6nifnde
A supervised learning framework for chromatin loop detection in genome-wide contact maps
2020
Nature Communications
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Current approaches are mainly focused on searching for statistically enriched dots on a genome-wide map. ...
We apply this framework to predict chromatin loops in 56 Hi-C datasets, and release the results at the 3D Genome Browser. ...
Job Dekker, William Noble, and the rest of 4D Nucleome Project Joint Analysis Workgroup for the discussion and suggestions. We thank Drs. ...
doi:10.1038/s41467-020-17239-9
pmid:32647330
pmcid:PMC7347923
fatcat:u6ludydumbdrzbycfjcvqedrve
A biochemically-interpretable machine learning classifier for microbial GWAS
2020
Nature Communications
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Here we present a metabolic model-based machine learning classifier, named Metabolic Allele Classifier (MAC), that uses flux balance analysis to estimate the biochemical effects of alleles. ...
Interpretation of MACs for three antibiotics (pyrazinamide, para-aminosalicylic acid, and isoniazid) recapitulates known AMR mechanisms and suggest a biochemical basis for how the identified alleles cause ...
Received: 6 August 2019; Accepted: 16 April 2020;
Acknowledgements We would like to thank Anand Sastry, Jean-Christophe Lachance, Yara Seif, and Jason Hyun for helpful discussions and Marc Abrams for ...
doi:10.1038/s41467-020-16310-9
pmid:32444610
fatcat:kohobbfcbngwbdjd4opsvwxiqm
GINOM: A statistical framework for assessing interval overlap of multiple genomic features
2017
PLoS Computational Biology
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Existing methodologies can test for significant pairwise associations between two genomic intervals; however, they cannot test for associations involving multiple sets of intervals. ...
A common problem in genomics is to test for associations between two or more genomic features, typically represented as intervals interspersed across the genome. ...
Acknowledgments The authors would like to thank Feifei Ding for data collection and assistance with the data analysis.
Author Contributions Conceptualization: DB QH NN. ...
doi:10.1371/journal.pcbi.1005586
pmid:28617797
pmcid:PMC5491313
fatcat:jwfvkghwyfgmtmjee7vrlc5xie
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