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Generalized random set framework for functional enrichment analysis using primary genomics datasets

Johannes M. Freudenberg, Siva Sivaganesan, Mukta Phatak, Kaustubh Shinde, Mario Medvedovic
2010 Computer applications in the biosciences : CABIOS  
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

Eugenia G Giannopoulou, Olivier Elemento
2011 BMC Bioinformatics  
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

Mikhail G. Dozmorov, Lukas R. Cara, Cory B. Giles, Jonathan D. Wren
2016 Bioinformatics  
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

Arunachalam Vinayagam, Travis E. Gibson, Ho-Joon Lee, Bahar Yilmazel, Charles Roesel, Yanhui Hu, Young Kwon, Amitabh Sharma, Yang-Yu Liu, Norbert Perrimon, Albert-László Barabási
2016 Proceedings of the National Academy of Sciences of the United States of America  
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

Zhong Wang, Huntington F Willard
2012 BMC Genomics  
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]

Samuel Katz, Jian Song, Kyle P. Webb, Nicolas W. Lounsbury, Clare E. Bryant, Iain D.C. Fraser
2020 bioRxiv   pre-print
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

Safoora Yousefi, Fatemeh Amrollahi, Mohamed Amgad, Chengliang Dong, Joshua E. Lewis, Congzheng Song, David A. Gutman, Sameer H. Halani, Jose Enrique Velazquez Vega, Daniel J. Brat, Lee A. D. Cooper
2017 Scientific Reports  
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

Damian Szklarczyk, Annika L Gable, David Lyon, Alexander Junge, Stefan Wyder, Jaime Huerta-Cepas, Milan Simonovic, Nadezhda T Doncheva, John H Morris, Peer Bork, Lars J Jensen, Christian von Mering
2018 Nucleic Acids Research  
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]

Safoora Yousefi, Fateme Amrollahi, Mohamed Amgad, Coco Dong, Joshua E Lewis, Congzheng Song, David A Gutman, Sameer H Halani, Jose Enrique Velazquez Vega, Daniel J Brat, Lee AD Cooper
2017 bioRxiv   pre-print
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

Shay Ben-Elazar, Zohar Yakhini, Itai Yanai
2013 Nucleic Acids Research  
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

SriGanesh Jammula, Diego Pasini
2016 Epigenetics & Chromatin  
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]

Vinsensius B. Vega, Yijun Ruan, Wing-Kin Sung
2008 Lecture Notes in Computer Science  
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

Tarik J. Salameh, Xiaotao Wang, Fan Song, Bo Zhang, Sage M. Wright, Chachrit Khunsriraksakul, Yijun Ruan, Feng Yue
2020 Nature Communications  
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

Erol S. Kavvas, Laurence Yang, Jonathan M. Monk, David Heckmann, Bernhard O. Palsson
2020 Nature Communications  
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

Darshan Bryner, Stephen Criscione, Andrew Leith, Quyen Huynh, Fred Huffer, Nicola Neretti, Satoru Miyano
2017 PLoS Computational Biology  
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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