WGAViewer[1] is a bioinformatics software tool which is designed to visualize, annotate, and help interpret the results generated from a genome wide association study (GWAS). Alongside the P values of association, WGAViewer allows a researcher to visualize and consider other supporting evidence, such as the genomic context of the SNP, linkage disequilibrium (LD) with ungenotyped SNPs, gene expression database, and the evidence from other GWAS projects, when determining the potential importance of an individual SNP.

Introduction

edit

Functions

edit

WGAViewer currently offers several classes of annotation of the GWAS results:

(1) Overview of WGA results allowing

  • zooming in/out
  • searching for gene/SNP
  • top hits sorting with individual SNP annotation

(2) Genic annotation of WGA results with explicit reference to:

  • align results with the latest genome build
  • gene/transcripts context[2]
  • linkage disequilibrium context [3]

(3) Annotation for SNPs :

  • LD score for all HapMap SNPs in specified region
  • association with specified gene expression [4]
  • SNP function information

(4) Gene/SNP finding : locating and annotating specific genes, SNPs, or LD proxies for SNPs, and aligning the results with the latest genome build.

(5) Evidence from multiple scans.

(6) Supporting/QC databases: displaying supporting information, for example, HWE P values, effect size, effect direction, QC scores, or other user-customized data.

Language

edit

WGAViewer is developed on the Java platform.

Authors

edit

WGAViewer is developed and maintained by Dr. Dongliang Ge and Dr. David B. Goldstein at Duke University, Institute for Genome Sciences & Policy, Center for Human Genome Variation.

Applications

edit

A number of GWAS projects [1] used the WGAViewer software tool.

One of these projects leads to the identification of the genetic variant predicting the hepatitis C treatment-induced viral clearance. The finding from that project, originally reported in Nature,[5] showed that genotype 1 hepatitis C patients carrying certain genetic variant alleles near the IL28B gene are more possibly to achieve sustained virological response after the treatment of Pegylated interferon-alpha-2a or Pegylated interferon-alpha-2b (brand names Pegasys or PEG-Intron) combined with ribavirin. A later report from Nature [6] demonstrated that the same genetic variants are also associated with the natural clearance of the genotype 1 hepatitis C virus.

References

edit
  1. ^ Ge D, Zhang K, Need AC, et al. (2008). "WGAViewer: software for genomic annotation of whole genome association studies". Genome Research. 18 (4): 640–643. doi:10.1101/gr.071571.107. PMC 2279251. PMID 18256235.
  2. ^ Hubbard TJ, Aken BL, Beal K, et al. (2007). "Ensembl 2007". Nucleic Acids Res. 35 (Database issue): D610–7. doi:10.1093/nar/gkl996. PMC 1761443. PMID 17148474.
  3. ^ The International HapMap Consortium (2007). "A second generation human haplotype map of over 3.1 million SNPs". Nature. 449 (7164): 851–61. Bibcode:2007Natur.449..851F. doi:10.1038/nature06258. PMC 2689609. PMID 17943122.
  4. ^ Stranger BE, Forrest MS, Clark AG, et al. (2005). "Genome-wide associations of gene expression variation in humans". PLOS Genet. 1 (6): e78. doi:10.1371/journal.pgen.0010078. PMC 1315281. PMID 16362079.
  5. ^ Ge D, Fellay J, Thompson AJ, et al. (2009). "Genetic variation in IL28B predicts hepatitis C treatment-induced viral clearance". Nature. 461 (7262): 399–401. Bibcode:2009Natur.461..399G. doi:10.1038/nature08309. PMID 19684573. S2CID 1707096.
  6. ^ Thomas DL, Thio CL, Martin MP, et al. (2009). "Genetic variation in IL28B and spontaneous clearance of hepatitis C virus". Nature. 461 (7265): 798–801. Bibcode:2009Natur.461..798T. doi:10.1038/nature08463. PMC 3172006. PMID 19759533.
edit