Some Capabilities for Model-Based and Model-Free Linkage Analysis using the Program Package S.A.G.E. (Statistical Analysis for Genetic Epidemiology)
Author(s) -
Amanda Schnell,
Xiangqing Sun,
Robert P. Igo,
Robert C. Elston
Publication year - 2011
Publication title -
human heredity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.423
H-Index - 62
eISSN - 1423-0062
pISSN - 0001-5652
DOI - 10.1159/000331672
Subject(s) - linkage (software) , trait , quantitative trait locus , genetics , genetic linkage , genetic epidemiology , inheritance (genetic algorithm) , biology , statistical model , genetic analysis , genetic model , computational biology , statistics , computer science , mathematics , gene , programming language
For both model-free and model-based linkage analysis the S.A.G.E. (Statistical Analysis for Genetic Epidemiology) program package has some unique capabilities in analyzing both continuous traits and binary traits with variable age of onset. Here we highlight model-based linkage analysis of a quantitative trait (plasma dopamine β hydroxylase) that is known to be largely determined by monogenic inheritance, using a prior segregation analysis to produce the best fitting model for the trait. For a binary trait with variable age of onset (schizophrenia), we illustrate how using age of onset information to obtain a quantitative susceptibility trait leads to more statistically significant linkage signals, suggesting better power.
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