SNPtoGO: characterizing SNPs by enriched GO terms | Zendy

Dániel Schwarz | Zendy; Oliver Hädicke | Zendy; Jeanette Erdmann | Zendy; Andreas Ziegler | Zendy; Daniel Bayer | Zendy; Steffen Möller | Zendy

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SNPtoGO: characterizing SNPs by enriched GO terms

Author(s) -

Dániel Schwarz,

Oliver Hädicke,

Jeanette Erdmann,

Andreas Ziegler,

Daniel Bayer,

Steffen Möller

Publication year - 2007

Publication title -

bioinformatics

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 3.599

H-Index - 390

eISSN - 1367-4811

pISSN - 1367-4803

DOI - 10.1093/bioinformatics/btm551

Subject(s) - computer science , computational biology , single nucleotide polymorphism , biology , genetics , gene , genotype

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.

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