SNPtoGO: Characterizing SNPs by enriched GO terms

Daniel F. Schwarz; Oliver Hädicke; Jeanette Erdmann; Andreas Ziegler; Daniel Bayer; Steffen Möller

doi:10.1093/bioinformatics/btm551

SNPtoGO: Characterizing SNPs by enriched GO terms

Daniel F. Schwarz^*, Oliver Hädicke, Jeanette Erdmann, Andreas Ziegler, Daniel Bayer, Steffen Möller

^*Korrespondierende/r Autor/-in für diese Arbeit

14 Zitate (Scopus)

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.

Originalsprache	Englisch
Zeitschrift	Bioinformatics
Jahrgang	24
Ausgabenummer	1
Seiten (von - bis)	146-148
Seitenumfang	3
ISSN	1367-4803
DOIs	https://doi.org/10.1093/bioinformatics/btm551
Publikationsstatus	Veröffentlicht - 01.01.2008

Fördermittel

This work was funded by the DFG (K02250/3–1) and the EU projects KnowARC (032691) and Cardiogenics (037593). The authors thank Thomas Martinetz, Silke Szymczak and the anonymous reviewers for their support and critical reading of the manuscript.

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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.",

author = "Schwarz, \{Daniel F.\} and Oliver H{\"a}dicke and Jeanette Erdmann and Andreas Ziegler and Daniel Bayer and Steffen M{\"o}ller",

note = "Funding Information: This work was funded by the DFG (K02250/3–1) and the EU projects KnowARC (032691) and Cardiogenics (037593). The authors thank Thomas Martinetz, Silke Szymczak and the anonymous reviewers for their support and critical reading of the manuscript.",

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doi = "10.1093/bioinformatics/btm551",

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AU - Schwarz, Daniel F.

AU - Hädicke, Oliver

AU - Erdmann, Jeanette

AU - Ziegler, Andreas

AU - Bayer, Daniel

AU - Möller, Steffen

N1 - Funding Information: This work was funded by the DFG (K02250/3–1) and the EU projects KnowARC (032691) and Cardiogenics (037593). The authors thank Thomas Martinetz, Silke Szymczak and the anonymous reviewers for their support and critical reading of the manuscript.

PY - 2008/1/1

Y1 - 2008/1/1

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.

AB - 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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DO - 10.1093/bioinformatics/btm551

M3 - Journal articles

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AN - SCOPUS:37549030905

SN - 1367-4803

VL - 24

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JO - Bioinformatics

JF - Bioinformatics

IS - 1

ER -

SNPtoGO: Characterizing SNPs by enriched GO terms

Abstract

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