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Typically, they consist of analyzing gene annotation frequencies in some pre-specified GO classes, in a class-by-class way, followed by p-value adjustment for multiple testing. Enrichment analysis, where a list of genes is compared against a wider universe of genes, is the most common example.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Results<\/jats:title>\n            <jats:p>A new global testing procedure and a method incorporating it are presented. Instead of testing separately for each GO class, a single global test for all classes under consideration is performed. The test is based on the distance between the functional profiles, defined as the joint frequencies of annotation in a given set of GO classes. These classes may be chosen at one or more GO levels. The new global test is more powerful and accurate with respect to type I errors than the usual class-by-class approach. When applied to some real datasets, the results suggest that the method may also provide useful information that complements the tests performed using a class-by-class approach if gene counts are sparse in some classes. An R library, <jats:italic>goProfiles<\/jats:italic>, implements these methods and is available from Bioconductor, <jats:ext-link xmlns:xlink=\"http:\/\/www.w3.org\/1999\/xlink\" xlink:href=\"http:\/\/bioconductor.org\/packages\/release\/bioc\/html\/goProfiles.html\" ext-link-type=\"uri\">http:\/\/bioconductor.org\/packages\/release\/bioc\/html\/goProfiles.html<\/jats:ext-link>.<\/jats:p>\n          <\/jats:sec>\n          <jats:sec>\n            <jats:title>Conclusions<\/jats:title>\n            <jats:p>The method provides an inferential basis for deciding whether two lists are functionally different. For global comparisons it is preferable to the global chi-square test of homogeneity. Furthermore, it may provide additional information if used in conjunction with class-by-class methods.<\/jats:p>\n          <\/jats:sec>","DOI":"10.1186\/1471-2105-12-401","type":"journal-article","created":{"date-parts":[[2011,12,3]],"date-time":"2011-12-03T03:03:57Z","timestamp":1322881437000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Comparison of lists of genes based on functional profiles"],"prefix":"10.1186","volume":"12","author":[{"given":"Miquel","family":"Salicr\u00fa","sequence":"first","affiliation":[]},{"given":"Jordi","family":"Oca\u00f1a","sequence":"additional","affiliation":[]},{"given":"Alex","family":"S\u00e1nchez-Pla","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2011,10,16]]},"reference":[{"key":"4944_CR1","first-page":"all","volume":"21","author":"S authors","year":"1999","unstructured":"authors S: The Chipping Forecast. 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