The goal of systems genetics is to understand the impact of genetic variation across all levels of biological organization, from mRNAs, proteins, and metabolites, to higher-order physiological and behavioral traits. This approach requires the accumulation and integration of many types of data, and also requires the use of many types of statistical tools to extract relevant patterns of covariation and causal relations as a function of genetics, environment, stage, and treatment. In this protocol we explain how to use the GeneNetwork web service, a powerful and free online resource for systems genetics. We provide workflows and methods to navigate massive multiscalar data sets and we explain how to use an extensive systems genetics toolkit for analysis and synthesis. Finally, we provide two detailed case studies that take advantage of human and mouse cohorts to evaluate linkage between gene variants, addiction, and aging.
Keywords: Allen Brain Atlas; BioGPS; GEO; GTEx; GWAS Catalog; Gemma; GeneRIF; GeneWeaver; Interval mapping; Manhattan plot; Metabolomics; Metagenomics; NCBI; PLINK; Pair scan; Principal component analysis; Proteomics; R/qtl; Recombinant inbred strain; Reverse genetics; Test cross; UCSC Genome Browser; WGCNA; WebGestalt; WebQTL; dbSNP; eQTL analysis.