[[File:Funrich.jpg|thumb|500px|none|Example of FunRich tool output. Image shows the result of comparing 4 different genes.]]
Specialized software tools for statistical analysis to determine the extent of over- or under-expression of a gene in a microarray experiment relative to a reference state have also been developed to aid in identifying genes or gene sets associated with particular [[phenotype]]s. One such method of analysis, known as [[Gene Set Enrichment]] Analysis (GSEA), uses a [[Kolmogorov-Smirnov]]-style statistic to identify groups of genes that are regulated together.<ref name=":0">{{cite journal |vauthors=Subramanian A, Tamayo P, Mootha VK, etal |title=Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles |journal=Proc. Natl. Acad. Sci. U.S.A. |volume=102 |issue=43 |pages=15545–50 |year=2005 |pmid=16199517 |doi=10.1073/pnas.0506580102 |pmc=1239896|doi-access=free }}</ref> This third-party statistics package offers the user information on the genes or gene sets of interest, including links to entries in databases such as NCBI's [[GenBank]] and curated databases such as Biocarta<ref>{{cite web |url=httpshttp://www.biocarta.com/ |title=BioCarta - Charting Pathways of Life |access-date=2007-12-31 }}</ref> and [[Gene Ontology]]. Protein complex enrichment analysis tool (COMPLEAT) provides similar enrichment analysis at the level of protein complexes.<ref>{{cite journal |vauthors=Vinayagam A, Hu Y, Kulkarni M, Roesel C, etal |title= Protein Complex-Based Analysis Framework for High-Throughput Data Sets. 6, rs5 (2013). |journal= Sci. Signal. |volume=6 |issue=r5 |year=2013 |pmid= 23443684 |doi= 10.1126/scisignal.2003629 |url= http://www.flyrnai.org/compleat/ |pages=rs5 |pmc=3756668}}</ref> The tool can identify the dynamic protein complex regulation under different condition or time points. Related system, PAINT<ref>{{cite web |url=http://www.dbi.tju.edu/dbi/staticpages.php?page=tools&menu=37 |title=DBI Web |access-date=2007-12-31 |url-status=dead |archive-url=https://web.archive.org/web/20070705061522/http://www.dbi.tju.edu/dbi/staticpages.php?page=tools |archive-date=2007-07-05 }}</ref> and SCOPE<ref>{{cite web |url=http://genie.dartmouth.edu/scope/ |title=SCOPE |access-date=2007-12-31 |archive-date=2011-08-17 |archive-url=https://web.archive.org/web/20110817031914/http://genie.dartmouth.edu/scope/ |url-status=dead }}</ref> performs a statistical analysis on gene promoter regions, identifying over and under representation of previously identified [[transcription factor]] response elements. Another statistical analysis tool is Rank Sum Statistics for Gene Set Collections (RssGsc), which uses rank sum probability distribution functions to find gene sets that explain experimental data.<ref>{{cite web |url=httphttps://rssgsc.sourceforge.net/ |title=RssGsc |access-date=2008-10-15 }}</ref> A further approach is contextual meta-analysis, i.e. finding out how a gene cluster responds to a variety of experimental contexts. [[Genevestigator]] is a public tool to perform contextual meta-analysis across contexts such as anatomical parts, stages of development, and response to diseases, chemicals, stresses, and [[neoplasms]].
