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The meaning of an affected GO group is often clearer than interpretations arising from a list of the statistically significant genes.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>Computer simulations demonstrated that correlations among genes invalidate many statistical methods that are commonly used to assign significance to GO terms. Ignoring these correlations overstates the statistical significance. Meta-analysis methods for combining p-values were modified to adjust for correlation. One of these methods is elaborated in the context of a comparison between two treatments. The form of the correlation adjustment depends upon the alternative hypothesis.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusion<\/jats:title>\n            <jats:p>Reliable corrections for the effect of correlations among genes on the significance level of a GO term can be constructed for an alternative hypothesis where all transcripts in the GO term increase (decrease) in response to treatment. For general alternatives, which allow some transcripts to increase and others to decrease, the bias of na\u00efve significance calculations can be greatly decreased although not eliminated.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-7-s2-s11","type":"journal-article","created":{"date-parts":[[2006,9,26]],"date-time":"2006-09-26T18:28:41Z","timestamp":1159295321000},"update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":32,"title":["A method for computing the overall statistical significance of a treatment effect among a group of genes"],"prefix":"10.1186","volume":"7","author":[{"given":"Robert","family":"Delongchamp","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Taewon","family":"Lee","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Cruz","family":"Velasco","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2006,9,26]]},"reference":[{"key":"1305_CR1","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/j.mrfmmm.2003.12.024","volume":"549","author":"W Tong","year":"2004","unstructured":"Tong W, Harris S, Cao X, Fang H, Shi L, Sun H, Fuscoe J, Harris A, Hong H, Xie Q, Perkins R, Casciano D: Development of public toxicogenomics software for microarray data management and analysis. 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