Fast Genome-Wide QTL Analysis Using Mendel

TL;DR

This paper introduces Mendel's optimized pedigree GWAS subroutine, enabling efficient, large-scale genome-wide QTL analysis for various data types, traits, and models, demonstrated on real and simulated datasets.

Contribution

The paper presents a highly efficient, versatile pedigree GWAS method in Mendel that handles complex data structures, multiple traits, and various genetic models, with robust features and practical performance.

Findings

Analysis of GAW19 data demonstrates Mendel's efficiency and accuracy.

Joint analysis of SBP and DBP traits completes in 78 minutes on a standard laptop.

Genome-wide eQTL analysis of 20,643 traits takes 30 hours on a cluster.

Abstract

Pedigree GWAS (Option 29) in the current version of the Mendel software is an optimized subroutine for performing large scale genome-wide QTL analysis. This analysis (a) works for random sample data, pedigree data, or a mix of both, (b) is highly efficient in both run time and memory requirement, (c) accommodates both univariate and multivariate traits, (d) works for autosomal and x-linked loci, (e) correctly deals with missing data in traits, covariates, and genotypes, (f) allows for covariate adjustment and constraints among parameters, (g) uses either theoretical or SNP-based empirical kinship matrix for additive polygenic effects, (h) allows extra variance components such as dominant polygenic effects and household effects, (i) detects and reports outlier individuals and pedigrees, and (j) allows for robust estimation via the $t$-distribution. The current paper assesses these capabilities on the genetics analysis workshop 19 (GAW19) sequencing data. We analyzed simulated and real phenotypes for both family and random sample data sets. For instance, when jointly testing the 8 longitudinally measured systolic blood pressure (SBP) and diastolic blood pressure (DBP) traits, it takes Mendel 78 minutes on a standard laptop computer to read, quality check, and analyze a data set with 849 individuals and 8.3 million SNPs. Genome-wide eQTL analysis of 20,643 expression traits on 641 individuals with 8.3 million SNPs takes 30 hours using 20 parallel runs on a cluster. Mendel is freely available at \url{http://www.genetics.ucla.edu/software}.