Association testing with Mendel.
This report presents an overview of association testing strategies from a user's perspective, with particular attention to the capabilities of the computer program Mendel. Association testing is driven by the nature of the study sample, the nature of the disease trait, and the kind of markers employed. The practicing statistician must also choose whether to conduct parametric or nonparametric tests. Because of the complexities involved, Mendel offers users several analysis options. The different options are tied together by shared input and output conventions and a shared language for defining models. Mendel also features new statistics and theory found in no other genetics software. The most important innovations include: association testing by penetrance estimation, expansion of matched-pair designs to permutation unit designs, and a rigorous implementation of the measured genotype approach for quantitative trait loci. This report explains how Mendel imputes allele counts and conducts both asymptotic and permutation tests in the measured genotype framework.
Lange
Kenneth
K
Department of Biomathematics, David Geffen School of Medicine at UCLA, Los Angeles, California 90095-7088, USA. klange@ucla.edu
Sinsheimer
Janet S
JS
Sobel
Eric
E
D000704:Analysis of Variance; D005787:Gene Frequency / Q000235:genetics; D005823:Genetics; D005838:Genotype; D006801:Humans; D008957:Models, Genetic; D019683:Penetrance; D020641:Polymorphism, Single Nucleotide / Q000235:genetics*; D040641:Quantitative Trait Loci / Q000235:genetics*; D012984:Software