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}
