A systematic strategy for the discovery of candidate genes responsible for phenotypic variation.
It is increasingly common to combine genome-wide expression data with quantitative trait mapping data to aid in the search for sequence polymorphisms responsible for phenotypic variation. By joining these complex but different data types at the level of the biological pathway, we can take advantage of existing biological knowledge to systematically identify possible mechanisms of genotype-phenotype interaction. With the development of web services and workflows, this process can be made rapid and systematic. Our methodology was applied to a use case of resistance to African trypanosomiasis in mice. Workflows developed in this investigation, including a guide to loading and executing them with example data, are available at http://www.myexperiment.org/users/43/workflows .
Fisher
Paul
P
School of Computer Science, University of Manchester, Manchester, UK.
Noyes
Harry
H
Kemp
Stephen
S
Stevens
Robert
R
Brass
Andrew
A
D000465:Algorithms; D000818:Animals; D020869:Gene Expression Profiling / Q000379:methods; D056726:Genetic Association Studies / Q000379:methods*; D018740:Genetic Heterogeneity; D020022:Genetic Predisposition to Disease; D006801:Humans; D051379:Mice; D010641:Phenotype; D040641:Quantitative Trait Loci / Q000235:genetics; D012984:Software; D014353:Trypanosomiasis, African / Q000235:genetics / Q000662:veterinary