Hello, after using statistical testing, we often obtain a list of genes. Could someone tell me what R/Bioconductor packages I can use to figure out what pathways/functions of these genes are in, e.g. a summary saying that 80% genes are related to breast cancer or 20% genes are related to glucose metabolism pathways? I guess these are GO-related packages. Thanks. - Ron

Dear Ron, If you have the functional annotations of your genes you may try RESEARCHER'S DIGEST: http://bioinfogp.cnb.csic.es/tools/digest It is a simple on-line tool that classify a list of genes in base on the similarities between their annotations (provided as input). DIGEST generates groups of genes that -in many cases- are functionally related. It is based on a set of text-mining rules that assign different degrees of biological relevance to each word in each annotation. The quality of the classification depends on the quality of the annotations but it works quite well with the typical gene descriptions currently provided by microarray manufacturers. The output of the system is not exactly what you asked for but -I hope- it may be useful for you. All the best, Juan Carlos Ron wrote: > Hello, after using statistical testing, we often obtain a list of genes. > Could someone tell me what R/Bioconductor packages I can use to figure > out what pathways/functions of these genes are in, e.g. a summary saying > that 80% genes are related to breast cancer or 20% genes are related to > glucose metabolism pathways? I guess these are GO-related packages. > > Thanks. - Ron > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor > -- Juan Carlos Oliveros BioinfoGP, CNB-CSIC ** NEW EMAIL ADDRESS: oliveros at cnb.csic.es **

Likely Bioconductor packages are GO.db and the organism-centric packages like org.Hs.eg.db, which contain 'maps' between various gene identifiers and GO terms. You might also find that GSEABase provides useful functions for creating gene sets representing looser concepts like 'related to breast cancer', perhaps using concepts defined in the Broad institute data base of gene sets (see ?getBroadSets) or (with the devel version of GSEABase) OBO-formated collections You'd likely use R scripts and / or the Category, GOstats, PGSEA or other packages to more formally assess whether there is meaningful signal in the represented pathways. Martin Ron <yzhu5 at="" wisc.edu=""> writes: > Hello, after using statistical testing, we often obtain a list of genes. > Could someone tell me what R/Bioconductor packages I can use to figure > out what pathways/functions of these genes are in, e.g. a summary saying > that 80% genes are related to breast cancer or 20% genes are related to > glucose metabolism pathways? I guess these are GO-related packages. > > Thanks. - Ron > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: http://news.gmane.org/gmane.science.biology.informatics.conductor -- Martin Morgan Computational Biology / Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N. PO Box 19024 Seattle, WA 98109 Location: Arnold Building M2 B169 Phone: (206) 667-2793