title: Diagnosis as a covariate in sib-pair linkage analysis.
abstract: A novel technique to detect significant covariates in linkage analysis using a logistic regression approach is illustrated. An overall test of linkage is first performed to determine whether there is significant perturbation from the expected 50% sharing in sib pairs. Covariates may include variables defined on the sib pair (multiple levels of diagnosis), covariates defined on the parents (parental diagnosis or gender of the transmitting parent), or indicators of study when analyzing multiple datasets to examine heterogeneity. A detailed example using a hierarchical diagnosis of severe, intermediate, mild, and unaffected is provided. This permits testing whether sib allele sharing differs by level of diagnosis and allows the use of discordant pairs to protect against marker allele misspecification.
authors: Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri 63110, USA. john@zork.wustl.edu
authors: J P
authors: JP
authors: Rice
mesh_terms: D008040:Genetic Linkage; D006801:Humans; D016015:Logistic Models; D016555:Matched-Pair Analysis; D001523:Mental Disorders / Q000235:genetics*; D020412:Multifactorial Inheritance; D009679:Nuclear Family