title: SNPtoGO: characterizing SNPs by enriched GO terms.
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.
  
  
  BACKGROUND
  A web interface and source code are offered at https://webtools.imbs.uni-luebeck.de/snptogo
authors.affiliation: Institut für Medizinische Biometrie und Statistik, Lübeck , Germany. schwarz@imbs.uni-luebeck.de
authors.forename: Daniel F
authors.initials: DF
authors.lastname: Schwarz
authors.forename: Oliver
authors.initials: O
authors.lastname: Hädicke
authors.forename: Jeanette
authors.initials: J
authors.lastname: Erdmann
authors.forename: Andreas
authors.initials: A
authors.lastname: Ziegler
authors.forename: Daniel
authors.initials: D
authors.lastname: Bayer
authors.forename: Steffen
authors.initials: S
authors.lastname: Möller
mesh_terms: D000465:Algorithms; D002874:Chromosome Mapping / Q000379:methods*; D004252:DNA Mutational Analysis; D030541:Databases, Genetic; D020869:Gene Expression Profiling / Q000379:methods*; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D012984:Software; D014584:User-Computer Interface