Determinants of QTL Mapping Power in the Realized Collaborative Cross

G3: Genes, Genomes, Genetics

Gregory R. Keele^1¹  Samir N. P. Kelada^2²  Wesley L. Crouse^1³  William Valdar^3⁵ 

[1] Curriculum in Bioinformatics and Computational Biology, University of North Carolina, Chapel Hill, North Carolina 27599;Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599;Department of Genetics, University of North Carolina, Chapel Hill, North Carolina 27599^1;Lineberger Comprehensive Cancer Center, University of North Carolina, Chapel Hill, North Carolina 27599^3;Marsico Lung Institute, University of North Carolina, Chapel Hill, North Carolina 27599^2

关键词: recombinant inbred lines;    haplotype association;    allelic series;    multiparental population;    MPP;    quantitative trait;    complex trait;    multiparent advanced generation inter-cross;    MAGIC;   

DOI  :  10.1534/g3.119.400194

学科分类：生物科学（综合）

来源: Genetics Society of America

【 摘 要 】

The Collaborative Cross (CC) is a mouse genetic reference population whose range of applications includes quantitative trait loci (QTL) mapping. The design of a CC QTL mapping study involves multiple decisions, including which and how many strains to use, and how many replicates per strain to phenotype, all viewed within the context of hypothesized QTL architecture. Until now, these decisions have been informed largely by early power analyses that were based on simulated, hypothetical CC genomes. Now that more than 50 CC strains are available and more than 70 CC genomes have been observed, it is possible to characterize power based on realized CC genomes. We report power analyses from extensive simulations and examine several key considerations: 1) the number of strains and biological replicates, 2) the QTL effect size, 3) the presence of population structure, and 4) the distribution of functionally distinct alleles among the founder strains at the QTL. We also provide general power estimates to aide in the design of future experiments. All analyses were conducted with our R package, SPARCC (Simulated Power Analysis in the Realized Collaborative Cross), developed for performing either large scale power analyses or those tailored to particular CC experiments.

【 授权许可】

CC BY