title: Fast genome-wide pedigree quantitative trait loci analysis using MENDEL.
abstract: The linkage era left a rich legacy of pedigree samples that can be used for modern genome-wide association sequencing (GWAS) or next-generation sequencing (NGS) studies. Family designs are naturally equipped to detect rare variants, control for population stratification, and facilitate the study of parent-of-origin effects. Unfortunately, pedigree likelihoods are notoriously hard to compute, and current software for association mapping in pedigrees is prohibitively slow in processing dense marker maps. In a recent release of the comprehensive genetic analysis software MENDEL, we implemented an ultra-fast score test for association mapping with pedigree-based GWAS or NGS study data. Our implementation (a) works for random sample data, pedigree data, or a mix of both;(b) allows for covariate adjustment, including correction for population stratification;(c) accommodates both univariate and multivariate quantitative traits; and (d) allows missing values in multivariate traits. In this paper, we assess the capabilities of MENDEL on the Genetic Analysis Workshop 18 sequencing data. For instance, when jointly testing the 4 longitudinally measured diastolic blood pressure traits, it takes MENDEL less than 51 minutes on a standard laptop computer to read, quality check, and analyze a data set with 959 individuals and 8.3 million single-nucleotide polymorphisms (SNPs). Our analysis reveals association of one SNP in the q32.2 region of chromosome 1. MENDEL is freely available on http://www.genetics.ucla.edu/software.
authors.affiliation: Department of Statistics, North Carolina State University, Raleigh, NC27695 USA.
authors.forename: Hua
authors.initials: H
authors.lastname: Zhou
authors.affiliation: Division of Epidemiology and Biostatistics, Mel and Enid Zuckerman College of Public Health, Tucson, AZ85721-0066, USA.
authors.forename: Jin
authors.initials: J
authors.lastname: Zhou
authors.affiliation: Department of Human Genetics, University of California, Los Angeles, CA90095, USA.
authors.forename: Eric M
authors.initials: EM
authors.lastname: Sobel
authors.affiliation: Department of Human Genetics, University of California, Los Angeles, CA90095, USA ; Department of Biomathematics, University of California, Los Angeles, CA90095, USA ; Department of Statistics, University of California, Los Angeles, CA90095, USA.
authors.forename: Kenneth
authors.initials: K
authors.lastname: Lange