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JOURNAL ARTICLE
S Ballouz, W Verleyen, J Gillis
MOTIVATION: RNA-seq co-expression analysis is in its infancy and reasonable practices remain poorly defined. We assessed a variety of RNA-seq expression data to determine factors affecting functional connectivity and topology in co-expression networks. RESULTS: We examine RNA-seq co-expression data generated from 1970 RNA-seq samples using a Guilt-By-Association framework, in which genes are assessed for the tendency of co-expression to reflect shared function. Minimal experimental criteria to obtain performance on par with microarrays were >20 samples with read depth >10 M per sample...
July 1, 2015: Bioinformatics
#2
JOURNAL ARTICLE
Fereydoun Hormozdiari, Osnat Penn, Elhanan Borenstein, Evan E Eichler
Despite considerable genetic heterogeneity underlying neurodevelopmental diseases, there is compelling evidence that many disease genes will map to a much smaller number of biological subnetworks. We developed a computational method, termed MAGI (merging affected genes into integrated networks), that simultaneously integrates protein-protein interactions and RNA-seq expression profiles during brain development to discover "modules" enriched for de novo mutations in probands. We applied this method to recent exome sequencing of 1116 patients with autism and intellectual disability, discovering two distinct modules that differ in their properties and associated phenotypes...
January 2015: Genome Research
#3
COMPARATIVE STUDY
Yang Chen, Xiang Zhang, Guo-Qiang Zhang, Rong Xu
Systems approaches to analyzing disease phenotype networks in combination with protein functional interaction networks have great potential in illuminating disease pathophysiological mechanisms. While many genetic networks are readily available, disease phenotype networks remain largely incomplete. In this study, we built a large-scale Disease Manifestation Network (DMN) from 50,543 highly accurate disease-manifestation semantic relationships in the United Medical Language System (UMLS). Our new phenotype network contains 2305 nodes and 373,527 weighted edges to represent the disease phenotypic similarities...
February 2015: Journal of Biomedical Informatics
#4
REVIEW
Hong-Dong Li, Rajasree Menon, Gilbert S Omenn, Yuanfang Guan
The vast majority of multi-exon genes in humans undergo alternative splicing, which greatly increases the functional diversity of protein species. Predicting functions at the isoform level is essential to further our understanding of developmental abnormalities and cancers, which frequently exhibit aberrant splicing and dysregulation of isoform expression. However, determination of isoform function is very difficult, and efforts to predict isoform function have been limited in the functional genomics field...
August 2014: Trends in Genetics: TIG
#5
COMPARATIVE STUDY
Kahn Rhrissorrakrai, Vincenzo Belcastro, Erhan Bilal, Raquel Norel, Carine Poussin, Carole Mathis, Rémi H J Dulize, Nikolai V Ivanov, Leonidas Alexopoulos, J Jeremy Rice, Manuel C Peitsch, Gustavo Stolovitzky, Pablo Meyer, Julia Hoeng
MOTIVATION: Inferring how humans respond to external cues such as drugs, chemicals, viruses or hormones is an essential question in biomedicine. Very often, however, this question cannot be addressed because it is not possible to perform experiments in humans. A reasonable alternative consists of generating responses in animal models and 'translating' those results to humans. The limitations of such translation, however, are far from clear, and systematic assessments of its actual potential are urgently needed...
February 15, 2015: Bioinformatics
#6
JOURNAL ARTICLE
Alex J Cornish, Florian Markowetz
Linking networks of molecular interactions to cellular functions and phenotypes is a key goal in systems biology. Here, we adapt concepts of spatial statistics to assess the functional content of molecular networks. Based on the guilt-by-association principle, our approach (called SANTA) quantifies the strength of association between a gene set and a network, and functionally annotates molecular networks like other enrichment methods annotate lists of genes. As a general association measure, SANTA can (i) functionally annotate experimentally derived networks using a collection of curated gene sets and (ii) annotate experimentally derived gene sets using a collection of curated networks, as well as (iii) prioritize genes for follow-up analyses...
September 2014: PLoS Computational Biology
#7
REVIEW
Wen-Hua Wei, Gibran Hemani, Chris S Haley
Genome-wide association studies (GWASs) have become the focus of the statistical analysis of complex traits in humans, successfully shedding light on several aspects of genetic architecture and biological aetiology. Single-nucleotide polymorphisms (SNPs) are usually modelled as having additive, cumulative and independent effects on the phenotype. Although evidently a useful approach, it is often argued that this is not a realistic biological model and that epistasis (that is, the statistical interaction between SNPs) should be included...
November 2014: Nature Reviews. Genetics
#8
JOURNAL ARTICLE
Hatice U Osmanbeyoglu, Raphael Pelossof, Jacqueline F Bromberg, Christina S Leslie
Cancer cells acquire genetic and epigenetic alterations that often lead to dysregulation of oncogenic signal transduction pathways, which in turn alters downstream transcriptional programs. Numerous methods attempt to deduce aberrant signaling pathways in tumors from mRNA data alone, but these pathway analysis approaches remain qualitative and imprecise. In this study, we present a statistical method to link upstream signaling to downstream transcriptional response by exploiting reverse phase protein array (RPPA) and mRNA expression data in The Cancer Genome Atlas (TCGA) breast cancer project...
November 2014: Genome Research
#9
JOURNAL ARTICLE
Frantisek Honti, Stephen Meader, Caleb Webber
Groupwise functional analysis of gene variants is becoming standard in next-generation sequencing studies. As the function of many genes is unknown and their classification to pathways is scant, functional associations between genes are often inferred from large-scale omics data. Such data types--including protein-protein interactions and gene co-expression networks--are used to examine the interrelations of the implicated genes. Statistical significance is assessed by comparing the interconnectedness of the mutated genes with that of random gene sets...
August 2014: PLoS Computational Biology
#10
COMMENT
Felix Muerdter, Alexander Stark
No abstract text is available yet for this article.
August 28, 2014: Nature
#11
JOURNAL ARTICLE
Carlos L Araya, Trupti Kawli, Anshul Kundaje, Lixia Jiang, Beijing Wu, Dionne Vafeados, Robert Terrell, Peter Weissdepp, Louis Gevirtzman, Daniel Mace, Wei Niu, Alan P Boyle, Dan Xie, Lijia Ma, John I Murray, Valerie Reinke, Robert H Waterston, Michael Snyder
Discovering the structure and dynamics of transcriptional regulatory events in the genome with cellular and temporal resolution is crucial to understanding the regulatory underpinnings of development and disease. We determined the genomic distribution of binding sites for 92 transcription factors and regulatory proteins across multiple stages of Caenorhabditis elegans development by performing 241 ChIP-seq (chromatin immunoprecipitation followed by sequencing) experiments. Integration of regulatory binding and cellular-resolution expression data produced a spatiotemporally resolved metazoan transcription factor binding map...
August 28, 2014: Nature
#12
COMPARATIVE STUDY
Mark B Gerstein, Joel Rozowsky, Koon-Kiu Yan, Daifeng Wang, Chao Cheng, James B Brown, Carrie A Davis, LaDeana Hillier, Cristina Sisu, Jingyi Jessica Li, Baikang Pei, Arif O Harmanci, Michael O Duff, Sarah Djebali, Roger P Alexander, Burak H Alver, Raymond Auerbach, Kimberly Bell, Peter J Bickel, Max E Boeck, Nathan P Boley, Benjamin W Booth, Lucy Cherbas, Peter Cherbas, Chao Di, Alex Dobin, Jorg Drenkow, Brent Ewing, Gang Fang, Megan Fastuca, Elise A Feingold, Adam Frankish, Guanjun Gao, Peter J Good, Roderic Guigó, Ann Hammonds, Jen Harrow, Roger A Hoskins, Cédric Howald, Long Hu, Haiyan Huang, Tim J P Hubbard, Chau Huynh, Sonali Jha, Dionna Kasper, Masaomi Kato, Thomas C Kaufman, Robert R Kitchen, Erik Ladewig, Julien Lagarde, Eric Lai, Jing Leng, Zhi Lu, Michael MacCoss, Gemma May, Rebecca McWhirter, Gennifer Merrihew, David M Miller, Ali Mortazavi, Rabi Murad, Brian Oliver, Sara Olson, Peter J Park, Michael J Pazin, Norbert Perrimon, Dmitri Pervouchine, Valerie Reinke, Alexandre Reymond, Garrett Robinson, Anastasia Samsonova, Gary I Saunders, Felix Schlesinger, Anurag Sethi, Frank J Slack, William C Spencer, Marcus H Stoiber, Pnina Strasbourger, Andrea Tanzer, Owen A Thompson, Kenneth H Wan, Guilin Wang, Huaien Wang, Kathie L Watkins, Jiayu Wen, Kejia Wen, Chenghai Xue, Li Yang, Kevin Yip, Chris Zaleski, Yan Zhang, Henry Zheng, Steven E Brenner, Brenton R Graveley, Susan E Celniker, Thomas R Gingeras, Robert Waterston
The transcriptome is the readout of the genome. Identifying common features in it across distant species can reveal fundamental principles. To this end, the ENCODE and modENCODE consortia have generated large amounts of matched RNA-sequencing data for human, worm and fly. Uniform processing and comprehensive annotation of these data allow comparison across metazoan phyla, extending beyond earlier within-phylum transcriptome comparisons and revealing ancient, conserved features. Specifically, we discover co-expression modules shared across animals, many of which are enriched in developmental genes...
August 28, 2014: Nature
#13
COMPARATIVE STUDY
Joshua W K Ho, Youngsook L Jung, Tao Liu, Burak H Alver, Soohyun Lee, Kohta Ikegami, Kyung-Ah Sohn, Aki Minoda, Michael Y Tolstorukov, Alex Appert, Stephen C J Parker, Tingting Gu, Anshul Kundaje, Nicole C Riddle, Eric Bishop, Thea A Egelhofer, Sheng'en Shawn Hu, Artyom A Alekseyenko, Andreas Rechtsteiner, Dalal Asker, Jason A Belsky, Sarah K Bowman, Q Brent Chen, Ron A-J Chen, Daniel S Day, Yan Dong, Andrea C Dose, Xikun Duan, Charles B Epstein, Sevinc Ercan, Elise A Feingold, Francesco Ferrari, Jacob M Garrigues, Nils Gehlenborg, Peter J Good, Psalm Haseley, Daniel He, Moritz Herrmann, Michael M Hoffman, Tess E Jeffers, Peter V Kharchenko, Paulina Kolasinska-Zwierz, Chitra V Kotwaliwale, Nischay Kumar, Sasha A Langley, Erica N Larschan, Isabel Latorre, Maxwell W Libbrecht, Xueqiu Lin, Richard Park, Michael J Pazin, Hoang N Pham, Annette Plachetka, Bo Qin, Yuri B Schwartz, Noam Shoresh, Przemyslaw Stempor, Anne Vielle, Chengyang Wang, Christina M Whittle, Huiling Xue, Robert E Kingston, Ju Han Kim, Bradley E Bernstein, Abby F Dernburg, Vincenzo Pirrotta, Mitzi I Kuroda, William S Noble, Thomas D Tullius, Manolis Kellis, David M MacAlpine, Susan Strome, Sarah C R Elgin, Xiaole Shirley Liu, Jason D Lieb, Julie Ahringer, Gary H Karpen, Peter J Park
Genome function is dynamically regulated in part by chromatin, which consists of the histones, non-histone proteins and RNA molecules that package DNA. Studies in Caenorhabditis elegans and Drosophila melanogaster have contributed substantially to our understanding of molecular mechanisms of genome function in humans, and have revealed conservation of chromatin components and mechanisms. Nevertheless, the three organisms have markedly different genome sizes, chromosome architecture and gene organization. On human and fly chromosomes, for example, pericentric heterochromatin flanks single centromeres, whereas worm chromosomes have dispersed heterochromatin-like regions enriched in the distal chromosomal 'arms', and centromeres distributed along their lengths...
August 28, 2014: Nature
#14
COMPARATIVE STUDY
Alan P Boyle, Carlos L Araya, Cathleen Brdlik, Philip Cayting, Chao Cheng, Yong Cheng, Kathryn Gardner, LaDeana W Hillier, Judith Janette, Lixia Jiang, Dionna Kasper, Trupti Kawli, Pouya Kheradpour, Anshul Kundaje, Jingyi Jessica Li, Lijia Ma, Wei Niu, E Jay Rehm, Joel Rozowsky, Matthew Slattery, Rebecca Spokony, Robert Terrell, Dionne Vafeados, Daifeng Wang, Peter Weisdepp, Yi-Chieh Wu, Dan Xie, Koon-Kiu Yan, Elise A Feingold, Peter J Good, Michael J Pazin, Haiyan Huang, Peter J Bickel, Steven E Brenner, Valerie Reinke, Robert H Waterston, Mark Gerstein, Kevin P White, Manolis Kellis, Michael Snyder
Despite the large evolutionary distances between metazoan species, they can show remarkable commonalities in their biology, and this has helped to establish fly and worm as model organisms for human biology. Although studies of individual elements and factors have explored similarities in gene regulation, a large-scale comparative analysis of basic principles of transcriptional regulatory features is lacking. Here we map the genome-wide binding locations of 165 human, 93 worm and 52 fly transcription regulatory factors, generating a total of 1,019 data sets from diverse cell types, developmental stages, or conditions in the three species, of which 498 (48...
August 28, 2014: Nature
#15
JOURNAL ARTICLE
Systematic analysis of somatic mutations in phosphorylation signaling predicts novel cancer drivers.
Jüri Reimand, Gary D Bader
No abstract text is available yet for this article.
2014: Molecular Systems Biology
#16
JOURNAL ARTICLE
Livnat Jerby-Arnon, Nadja Pfetzer, Yedael Y Waldman, Lynn McGarry, Daniel James, Emma Shanks, Brinton Seashore-Ludlow, Adam Weinstock, Tamar Geiger, Paul A Clemons, Eyal Gottlieb, Eytan Ruppin
Synthetic lethality occurs when the inhibition of two genes is lethal while the inhibition of each single gene is not. It can be harnessed to selectively treat cancer by identifying inactive genes in a given cancer and targeting their synthetic lethal (SL) partners. We present a data-driven computational pipeline for the genome-wide identification of SL interactions in cancer by analyzing large volumes of cancer genomic data. First, we show that the approach successfully captures known SL partners of tumor suppressors and oncogenes...
August 28, 2014: Cell
#17
JOURNAL ARTICLE
Vladimir Gligorijević, Vuk Janjić, Nataša Pržulj
MOTIVATION: Recently, a shift was made from using Gene Ontology (GO) to evaluate molecular network data to using these data to construct and evaluate GO. Dutkowski et al. provide the first evidence that a large part of GO can be reconstructed solely from topologies of molecular networks. Motivated by this work, we develop a novel data integration framework that integrates multiple types of molecular network data to reconstruct and update GO. We ask how much of GO can be recovered by integrating various molecular interaction data...
September 1, 2014: Bioinformatics
#18
JOURNAL ARTICLE
Ming Ni, Fuqiang Ye, Juanjuan Zhu, Zongwei Li, Shuai Yang, Bite Yang, Lu Han, Yongge Wu, Ying Chen, Fei Li, Shengqi Wang, Xiaochen Bo
MOTIVATION: Numerous public microarray datasets are valuable resources for the scientific communities. Several online tools have made great steps to use these data by querying related datasets with users' own gene signatures or expression profiles. However, dataset annotation and result exhibition still need to be improved. RESULTS: ExpTreeDB is a database that allows for queries on human and mouse microarray experiments from Gene Expression Omnibus with gene signatures or profiles...
December 1, 2014: Bioinformatics
#19
LETTER
Steven W Cole, Barbara L Fredrickson
No abstract text is available yet for this article.
September 2, 2014: Proceedings of the National Academy of Sciences of the United States of America
#20
JOURNAL ARTICLE
Nicholas J L Brown, Douglas A MacDonald, Manoj Pratim Samanta, Harris L Friedman, James C Coyne
Fredrickson et al. [Fredrickson BL, et al. (2013) Proc Natl Acad Sci USA 110(33):13684-13689] claimed to have observed significant differences in gene expression related to hedonic and eudaimonic dimensions of well-being. Having closely examined both their claims and their data, we draw substantially different conclusions. After identifying some important conceptual and methodological flaws in their argument, we report the results of a series of reanalyses of their dataset. We first applied a variety of exploratory and confirmatory factor analysis techniques to their self-reported well-being data...
September 2, 2014: Proceedings of the National Academy of Sciences of the United States of America
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