Summary: Traditional methods of genetic study design and analysis work well under the scenario that a handful of single nucleotide polymorphisms (SNPs) independently contribute to the risk of disease. For complex diseases, susceptibility may be determined not by a single SNP, but rather a complex interplay between SNPs. For large studies involving hundreds of thousands of SNPs, a brute force search of all possible combinations of SNPs associated with disease is not only inefficient, but also results in a multiple testing paradigm, whereby larger and larger sample sizes are needed to maintain statistical power. Pathway-based methods are an example of one of the many approaches in identifying a subset of SNPs to test for interaction. To help determine which SNP–SNP interactions to test, we developed Path, a software application designed to help researchers interface their data with biological information from several bioinformatics resources. To this end, our application brings together currently available information from nine online bioinformatics resources including the National Center for Biotechnology Information (NCBI), Online Mendelian Inheritance in Man (OMIM), Kyoto Encyclopedia of Genes and Genomes (KEGG), UCSC Genome Browser, Seattle SNPs, PharmGKB, Genetic Association Database, the Single Nucleotide Polymorphism database (dbSNP) and the Innate Immune Database (IIDB). Availability: The software, example datasets and tutorials are freely available from http://genapha.icapture.ubc.ca/PathTutorial. Contact: ddaley@mrl.ubc.ca
[1]
Hiroyuki Ogata,et al.
KEGG: Kyoto Encyclopedia of Genes and Genomes
,
1999,
Nucleic Acids Res..
[2]
Kiyoko F. Aoki-Kinoshita,et al.
From genomics to chemical genomics: new developments in KEGG
,
2005,
Nucleic Acids Res..
[3]
Manuel A. R. Ferreira,et al.
PLINK: a tool set for whole-genome association and population-based linkage analyses.
,
2007,
American journal of human genetics.
[4]
Mark Daly,et al.
Haploview: analysis and visualization of LD and haplotype maps
,
2005,
Bioinform..
[5]
Frank Dudbridge,et al.
Likelihood-Based Association Analysis for Nuclear Families and Unrelated Subjects with Missing Genotype Data
,
2008,
Human Heredity.
[6]
Yoshihiro Yamanishi,et al.
KEGG for linking genomes to life and the environment
,
2007,
Nucleic Acids Res..
[7]
Jurg Ott,et al.
Handbook of Human Genetic Linkage
,
1994
.
[8]
G. Abecasis,et al.
A general test of association for quantitative traits in nuclear families.
,
2000,
American journal of human genetics.
[9]
F. Dudbridge.
Pedigree disequilibrium tests for multilocus haplotypes
,
2003,
Genetic epidemiology.