Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

被引:11276
作者
Huang, Da Wei [1 ]
Sherman, Brad T. [1 ]
Lempicki, Richard A. [1 ]
机构
[1] Natl Canc Inst, Lab Immunopathogenesis & Bioinformat, Clin Serv Program, SAIC Frederick Inc, Ft Detrick, MD 21702 USA
关键词
EXPRESSION DATA; SET ENRICHMENT; ONTOLOGY TERMS; MICROARRAY DATA; WEB TOOL; BIOLOGICAL INTERPRETATION; STATISTICAL-ANALYSIS; GENOMIC ANALYSIS; ANNOTATION; INFORMATION;
D O I
10.1093/nar/gkn923
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:1 / 13
页数:13
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