Human Linkage and Association Analysis
- DOI:
- 10.1093/med/9780190221973.003.0005
The basic idea in linkage analysis is that a disease gene will segregate in a family with a close (linked) marker, and typing this marker will lead to its detection. The successes using this approach have been largely confined to Mendelian monogenic disorders or complex disorders with Mendelian subforms. During the last decade, psychiatric genetics abandoned linkage analysis and moved to case-control studies of association, with remarkable success in identifying susceptibility genes for mental disorders. In this chapter, we review the statistical underpinnings of linkage and association and discuss important issues such as population stratification, imputation, data cleaning, the genomic inflation factor, and QQ and Manhattan plots. The challenge for the next decade will be to understand the biology of these GWAS (genome-wide association study) hits.
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