SEQSpark: A Complete Analysis Tool for Large-Scale Rare Variant Association Studies using Whole-Genome and Exome Sequence Data

Massively parallel sequencing technologies provide great opportunities for discovering rare susceptibility variants involved in complex disease etiology via large-scale imputation and exome and whole-genome sequence-based association studies. Due to modest effect sizes, large sample sizes of tens to hundreds of thousands of individuals are required for adequately powered studies. Current analytical tools are obsolete when it comes to handling these large datasets. To facilitate the analysis of large-scale sequence-based studies, we developed SEQSpark which implements parallel processing based on Spark to increase the speed and efficiency of performing data quality control, annotation, and association analysis.

Source: The American Journal of Human Genetics - June 29, 2017 Category: Genetics & Stem Cells Authors: Di Zhang, Linhai Zhao, Biao Li, Zongxiao He, Gao T. Wang, Dajiang J. Liu, Suzanne M. Leal Tags: Report Source Type: research