Genome Wide Association Study (GWAS)

Background

The human genome contains hundreds of millions of single-nucleotide polymorphisms (SNPs) as well as many thousands more variations in the number of copies of small and large genomic segments (copy number variations or CNVs).  Genome Wide Association Studies (GWA studies or GWAS) allow researchers to sample up to a million or more SNPs from each subject in a study capturing variation uniformly across the genome. To date, these studies have identified risks and protective factors for asthma, cancer, diabetes, heart disease, mental illness and other human conditions.

GWAS are used to compare a large number of SNPs of two groups of participants with different phenotype, for example individuals suffering from some medical conditions (cases) and healthy individuals (controls). Each person gives a sample of cells, such as swabs of cells from the inside of the cheek. DNA is extracted from these cells, and spread on SNP microarrays, which can classify (genotype) up to a million of individual SNPs. The data from these microarrays are read into computers, where they can be analyzed using a variety of bioinformatic tools and techniques.

Analysis

Simbiot provides functionality to perform GWAS on data generated using Affymetrix and Illumina SNP microarrays.  The analysis is implemented using the algorithms published in the Bioconductor (Gentleman, Carey et al. 2004) snpMatrix (Clayton and Leung 2007) library. 

Free demo accounts are available at http://www.simbiot.net.

Please also see more information about Simbiot Single User Accounts and Private Server installations as well as a brief introduction to microarray analysis.

References

Clayton, D. and H. T. Leung (2007). "An R package for analysis of whole-genome association studies." Hum Hered 64(1): 45-51.

Gentleman, R. C., V. J. Carey, et al. (2004). "Bioconductor: open software development for computational biology and bioinformatics." Genome Biol 5(10): R80.