Year: 2014
Type: article
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.
Source: BMC Proceedings
Authors: Hua Zhou, Jin Zhou, Eric M Sobel, Kenneth Lange
Language: English
Subfield: Genetics
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $2,290
Awards: Multiethnic Study of Type 2 Diabetes Genes, Identifying T2D Variants by DNA Sequencing in Multiethnic Samples, Identification and Replication of Type 2 Diabetes Genes in Mexican Americans, Discovery of Functional Variants in Type 2 Diabetes Genes in Mexican Americans, Identifying variants causal for Type 2 Diabetes in Major human populations, NIDDM Susceptibility Genes in Mexican Americans, Statistical Methods for Gene Mapping, Tensor Regressions and Applications in Neuroimaging Data Analysis, Genetics of Gallbladder Disease in Mexican Americans, G725404114, Genetic Analysis of Common Diseases: An Evaluation, Genomics, EHRs, GPUs, and Next Generation Computational Statistics
OpenAlex ID: W2088104815