Visually integrating and exploring high throughput Phenome-Wide Association Study (PheWAS) results using PheWAS-View

Sarah A. Pendergrass, Scott M. Dudek, Dana C. Crawford, Marylyn Deriggi Ritchie

Research output: Contribution to journalArticle

29 Citations (Scopus)

Abstract

Background: Phenome-Wide Association Studies (PheWAS) can be used to investigate the association between single nucleotide polymorphisms (SNPs) and a wide spectrum of phenotypes. This is a complementary approach to Genome Wide Association studies (GWAS) that calculate the association between hundreds of thousands of SNPs and one or a limited range of phenotypes. The extensive exploration of the association between phenotypic structure and genotypic variation through PheWAS produces a set of complex and comprehensive results. Integral to fully inspecting, analysing, and interpreting PheWAS results is visualization of the data. Results: We have developed the software PheWAS-View for visually integrating PheWAS results, including information about the SNPs, relevant genes, phenotypes, and the interrelationships between phenotypes, that exist in PheWAS. As a result both the fine grain detail as well as the larger trends that exist within PheWAS results can be elucidated. Conclusions: PheWAS can be used to discover novel relationships between SNPs, phenotypes, and networks of interrelated phenotypes; identify pleiotropy; provide novel mechanistic insights; and foster hypothesis generation and these results can be both explored and presented with PheWAS-View. PheWAS-View is freely available for non-commercial research institutions, for full details see http://ritchielab.psu.edu/ritchielab/software.

Original languageEnglish (US)
Article number5
JournalBioData Mining
Volume5
Issue number1
DOIs
StatePublished - Jun 12 2012

Fingerprint

Nucleotides
Polymorphism
High Throughput
Throughput
Phenotype
Single Nucleotide Polymorphism
Genes
Single nucleotide Polymorphism
Software
Visualization
Genome-Wide Association Study
Research
Genome

All Science Journal Classification (ASJC) codes

  • Biochemistry
  • Molecular Biology
  • Genetics
  • Computer Science Applications
  • Computational Theory and Mathematics
  • Computational Mathematics

Cite this

Pendergrass, Sarah A. ; Dudek, Scott M. ; Crawford, Dana C. ; Ritchie, Marylyn Deriggi. / Visually integrating and exploring high throughput Phenome-Wide Association Study (PheWAS) results using PheWAS-View. In: BioData Mining. 2012 ; Vol. 5, No. 1.
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Visually integrating and exploring high throughput Phenome-Wide Association Study (PheWAS) results using PheWAS-View. / Pendergrass, Sarah A.; Dudek, Scott M.; Crawford, Dana C.; Ritchie, Marylyn Deriggi.

In: BioData Mining, Vol. 5, No. 1, 5, 12.06.2012.

Research output: Contribution to journalArticle

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