Insight into genetic contributions to common, complex diseases of increasing public health importance such as asthma, diabetes and cardiovascular disease, is growing relatively slowly. Practical access barriers to newer bioinformatic resources and to appropriate statistical methods impede progress. Leveraging the existing R language and Bioconductor framework, an integrated suite of applications supporting activities common to complex disease association research will be created, directly addressing those barriers.
Specific aims i nclude software support for importing experimental data and genomic annotation; methods for statistical power calculations and for selecting maximally informative subsets of markers during experimental design; methods for visualizing and summarizing experimental results; established and recently developed methods supporting statistical inference on single markers, multiple markers and on the epistatic and gene by environment interactions characteristic of these diseases and needed for emerging fields of study such as pharmacogenetics. These deliverables will share a coherent user interface and common data structures, and will be accompanied by tutorials, example code and data, introductory and advanced documentation for users, and detailed source code and technical documentation for methods developers. The resulting packages will be widely distributed through the existing Bioconductor network and through the I(2)B(2) NCBC, as an immediately usable, open-source, interoperable and flexible genetic association experimental design and analysis software suite. Method developers will gain access to an integrated framework and a user base for building and distributing their work. Researchers will gain free and ready access to an increasingly rich range of bioinformatic resources and new statistical methods for genetic association analysis, because many existing practical challenges in their installation and use will have been overcome. Developed in the context of airways disease, the software will be immediately and directly applicable to genetic research in other common, complex disorders.
