Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists
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TLDR
The survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.Abstract:
Functional analysis of large gene lists, derived in most cases from emerging high-throughput genomic, proteomic and bioinformatics scanning approaches, is still a challenging and daunting task. The gene-annotation enrichment analysis is a promising high-throughput strategy that increases the likelihood for investigators to identify biological processes most pertinent to their study. Approximately 68 bioinformatics enrichment tools that are currently available in the community are collected in this survey. Tools are uniquely categorized into three major classes, according to their underlying enrichment algorithms. The comprehensive collections, unique tool classifications and associated questions/issues will provide a more comprehensive and up-to-date view regarding the advantages, pitfalls and recent trends in a simpler tool-class level rather than by a tool-by-tool approach. Thus, the survey will help tool designers/developers and experienced end users understand the underlying algorithms and pertinent details of particular tool categories/tools, enabling them to make the best choices for their particular research interests.read more
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Journal ArticleDOI
Metascape provides a biologist-oriented resource for the analysis of systems-level datasets.
Yingyao Zhou,Bin Zhou,Lars Pache,Max W. Chang,Alireza Hadj Khodabakhshi,Olga Tanaseichuk,Christopher Benner,Sumit K. Chanda +7 more
TL;DR: A biologist-oriented portal that provides a gene list annotation, enrichment and interactome resource and enables integrated analysis of multi-OMICs datasets, Metascape is an effective and efficient tool for experimental biologists to comprehensively analyze and interpret OMICs-based studies in the big data era.
Journal ArticleDOI
Enrichr: a comprehensive gene set enrichment analysis web server 2016 update
Maxim V. Kuleshov,Matthew R. Jones,Andrew D. Rouillard,Nicolas F. Fernandez,Qiaonan Duan,Zichen Wang,Simon Koplev,Sherry L. Jenkins,Kathleen M. Jagodnik,Alexander Lachmann,Michael G. McDermott,Caroline D. Monteiro,Gregory W. Gundersen,Avi Ma'ayan +13 more
TL;DR: A significant update to one of the tools in this domain called Enrichr, a comprehensive resource for curated gene sets and a search engine that accumulates biological knowledge for further biological discoveries is presented.
Journal ArticleDOI
GSVA: gene set variation analysis for microarray and RNA-seq data.
TL;DR: This work introduces Gene Set Variation Analysis (GSVA), a GSE method that estimates variation of pathway activity over a sample population in an unsupervised manner and constitutes a starting point to build pathway-centric models of biology.
Journal ArticleDOI
The Molecular Signatures Database Hallmark Gene Set Collection
Arthur Liberzon,Chet Birger,Helga Thorvaldsdottir,Mahmoud Ghandi,Jill P. Mesirov,Pablo Tamayo +5 more
TL;DR: A combination of automated approaches and expert curation is used to develop a collection of "hallmark" gene sets, derived from multiple "founder" sets, that conveys a specific biological state or process and displays coherent expression in MSigDB.
Journal ArticleDOI
The Reactome Pathway Knowledgebase.
Antonio Fabregat,Konstantinos Sidiropoulos,Phani V. Garapati,Marc Gillespie,Marc Gillespie,Kerstin Hausmann,Robin Haw,Bijay Jassal,S Jupe,Florian Korninger,Sheldon J. McKay,Lisa Matthews,Bruce May,Marija Milacic,Karen Rothfels,Veronica Shamovsky,Marissa Webber,Joel Weiser,Mark Williams,Guanming Wu,Lincoln Stein,Lincoln Stein,Lincoln Stein,Henning Hermjakob,Henning Hermjakob,Peter D'Eustachio +25 more
TL;DR: The Reactome Knowledgebase provides molecular details of signal transduction, transport, DNA replication, metabolism and other cellular processes as an ordered network of molecular transformations—an extended version of a classic metabolic map, in a single consistent data model.
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