New joint covariance- and marginal-based tests for association and linkage for quantitative traits for random and non-random sampling.
We develop novel statistical tests for transmission disequilibrium testing (tests of linkage in the presence of association) for quantitative traits using parents and offspring. These joint tests utilize information in both the covariance (or more generally, dependency) between genotype and phenotype and the marginal distribution of genotype. Using computer simulation we test the validity (Type I error rate control) and power of the proposed methods, for additive, dominant, and recessive modes of inheritance, locus-specific heritability of the trait 0.05, 0.1, 0.2 with allele frequencies of P=0.2 and 0.4, and sample sizes of 500, 200, and 100 trios. Both random sampling and extreme sampling schemes were investigated. A multinomial logistic joint test provides the highest overall power irrespective of sample size, allele frequency, heritability, and modes of inheritance.
Tiwari
Hemant K
HK
Department of Biostatistics, Section on Statistical Genetics, University of Alabama at Birmingham, Birmingham, Alabama 35294, USA. htiwari@uab.edu
Holt
Janet
J
George
Varghese
V
Beasley
T Mark
TM
Amos
Christopher I
CI
Allison
David B
DB
D000465:Algorithms; D000704:Analysis of Variance; D003198:Computer Simulation / Q000706:statistics & numerical data; D005787:Gene Frequency; D008040:Genetic Linkage / Q000235:genetics*; D005838:Genotype; D006801:Humans; D015810:Linkage Disequilibrium; D016015:Logistic Models; D010641:Phenotype; D040641:Quantitative Trait Loci / Q000235:genetics*; D015983:Selection Bias