SNPtoGO: characterizing SNPs by enriched GO terms

by: Daniel F Schwarz, Oliver Hadicke, Jeanette Erdmann, Andreas Ziegler, Daniel Bayer, Steffen Moller

Bioinformatics, Vol. 24, No. 1. (1 January 2008), pp. 146-148.

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Abstract

For the analysis of complex polygenic diseases, one does not expect all patients to share the same disease-associated alleles. Not even will disease-causing variations be assigned to the identical sets of genes between patients. However, one does expect overlaps in the sets of genes that are involved and even more so in their assigned molecular processes. Furthermore, the assignment of single nucleotide polymorphisms (SNPs) to genes is highly ambiguous for intergenic SNPs. The tool presented here hence adds external information, i.e. GeneOntology (GO) terms (Gene Ontology Consortium), to the analysis of SNP data. Availability: A web interface and source code are offered at https://webtools.imbs.uni-luebeck.de/snptogo Contact: schwarz@imbs.uni-luebeck.de 10.1093/bioinformatics/btm551

@article{citeulike:2149865, abstract = {For the analysis of complex polygenic diseases, one does not expect all patients to share the same disease-associated alleles. Not even will disease-causing variations be assigned to the identical sets of genes between patients. However, one does expect overlaps in the sets of genes that are involved and even more so in their assigned molecular processes. Furthermore, the assignment of single nucleotide polymorphisms (SNPs) to genes is highly ambiguous for intergenic SNPs. The tool presented here hence adds external information, i.e. GeneOntology (GO) terms (Gene Ontology Consortium), to the analysis of SNP data. Availability: A web interface and source code are offered at https://webtools.imbs.uni-luebeck.de/snptogo Contact: schwarz@imbs.uni-luebeck.de 10.1093/bioinformatics/btm551}, author = {Schwarz, Daniel F. and Hadicke, Oliver and Erdmann, Jeanette and Ziegler, Andreas and Bayer, Daniel and Moller, Steffen }, citeulike-article-id = {2149865}, doi = {10.1093/bioinformatics/btm551}, journal = {Bioinformatics}, month = {January}, number = {1}, pages = {146--148}, posted-at = {2008-01-08 03:08:44}, priority = {2}, title = {SNPtoGO: characterizing SNPs by enriched GO terms}, url = {http://dx.doi.org/10.1093/bioinformatics/btm551}, volume = {24}, year = {2008} }

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TY - JOUR ID - citeulike:2149865 L3 - citeulike-article-id:2149865 TI - SNPtoGO: characterizing SNPs by enriched GO terms JF - Bioinformatics VL - 24 IS - 1 SP - 146 EP - 148 N2 - For the analysis of complex polygenic diseases, one does not expect all patients to share the same disease-associated alleles. Not even will disease-causing variations be assigned to the identical sets of genes between patients. However, one does expect overlaps in the sets of genes that are involved and even more so in their assigned molecular processes. Furthermore, the assignment of single nucleotide polymorphisms (SNPs) to genes is highly ambiguous for intergenic SNPs. The tool presented here hence adds external information, i.e. GeneOntology (GO) terms (Gene Ontology Consortium), to the analysis of SNP data. Availability: A web interface and source code are offered at https://webtools.imbs.uni-luebeck.de/snptogo Contact: schwarz@imbs.uni-luebeck.de 10.1093/bioinformatics/btm551 AU - Schwarz, Daniel AU - Hadicke, Oliver AU - Erdmann, Jeanette AU - Ziegler, Andreas AU - Bayer, Daniel AU - Moller, Steffen PY - 2008/01/01/ UR - http://dx.doi.org/10.1093/bioinformatics/btm551 ER -

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