PT - JOURNAL ARTICLE AU - Qingyu Wang AU - Cooduvalli S. Shashikant AU - Naomi S. Altman AU - Santhosh Girirajan TI - Novel metrics to measure coverage in whole exome sequencing datasets reveal local and global non-uniformity AID - 10.1101/051888 DP - 2016 Jan 01 TA - bioRxiv PG - 051888 4099 - http://biorxiv.org/content/early/2016/05/05/051888.short 4100 - http://biorxiv.org/content/early/2016/05/05/051888.full AB - Whole Exome Sequencing (WES) is a powerful clinical diagnostic tool for discovering the genetic basis of many diseases. A major shortcoming of WES is uneven coverage of sequence reads over the exome targets contributing to many low coverage regions, which hinders accurate variant calling. In this study, we devised two novel metrics, Cohort Coverage Sparseness (CCS) and Unevenness (UE) Scores for a detailed assessment of the distribution of coverage of sequence reads. Employing these metrics we revealed non-uniformity of coverage in the WES data generated by three different platforms. This non-uniformity of coverage is both local (coverage of a given exon across different platforms) and global (coverage of all exons across the genome in the given platform). The low coverage regions encompassing functionally important genes were often associated with high GC content, repeat elements and segmental duplications. Some of the problems associated with WES are due to extrapolation of technologies primarily designed for Whole Genome Sequencing platforms. Further refinements in these technologies have potential to enhance the clinical applications of WES platforms.