The Cross-Platform Association Toolkit (XPAT), provides a suite of tools designed to support and conduct large-scale association studies with heterogeneous sequencing datasets. XPAT includes tools to support cross-platform aware variant calling, quality control filtering, gene-based association testing, and rare variant effect size estimation. The data alignment and variant calling module in XPAT provides automated parallel computing workflows that interface with the Burrows-Wheeler Aligner (BWA) (v0.7.9a), the Genome Analysis Toolkit (GATK) (v3.3), and other tools to filter low quality sequencing reads and to align cleaned reads to a reference genome. The automated quality control module, XQC, involve a series of analyses to identify and filter problematic samples and variants due to cross-platform biases. XQC also conducts automated Principle Component Analysis and incorporates the principle components in subsequent association tests. The association test module, XATC, supports 29 gene-based rare variant association tests, as well as single marker tests using linear and logistic regression. The effect size estimate module, XES, can estimate odds ratios (ORs) for particular classes of rare variants in a gene, including likely gene disrupting (LGD) variants and missense variants predicted to be damaging from in silico<\i> functional prediction tools, including PolyPhen2 and VAAST CASM scores.
XPAT: a toolkit to conduct cross-platform association studies with heterogeneous sequencing datasets. In: Nucleic Acids Research, 2017.