Characterizing reduced coverage regions through comparison of exome and genome sequencing data across 10 centers.

TitleCharacterizing reduced coverage regions through comparison of exome and genome sequencing data across 10 centers.
Publication TypeJournal Article
Year of Publication2017
AuthorsSanghvi, RV, Buhay, CJ, Powell, BC, Tsai, EA, Dorschner, MO, Hong, CS, Lebo, MS, Sasson, A, Hanna, DS, McGee, S, Bowling, KM, Cooper, GM, Gray, DE, Lonigro, RJ, Dunford, A, Brennan, CA, Cibulskis, C, Walker, K, Carneiro, MO, Sailsbery, J, Hindorff, LA, Robinson, DR, Santani, A, Sarmady, M, Rehm, HL, Biesecker, LG, Nickerson, DA, Hutter, CM, Garraway, L, Muzny, DM, Wagle, N
JournalGenet Med
Date Published2017 Nov 16
ISSN1530-0366
Abstract

PurposeAs massively parallel sequencing is increasingly being used for clinical decision making, it has become critical to understand parameters that affect sequencing quality and to establish methods for measuring and reporting clinical sequencing standards. In this report, we propose a definition for reduced coverage regions and describe a set of standards for variant calling in clinical sequencing applications.MethodsTo enable sequencing centers to assess the regions of poor sequencing quality in their own data, we optimized and used a tool (ExCID) to identify reduced coverage loci within genes or regions of particular interest. We used this framework to examine sequencing data from 500 patients generated in 10 projects at sequencing centers in the National Human Genome Research Institute/National Cancer Institute Clinical Sequencing Exploratory Research Consortium.ResultsThis approach identified reduced coverage regions in clinically relevant genes, including known clinically relevant loci that were uniquely missed at individual centers, in multiple centers, and in all centers.ConclusionThis report provides a process road map for clinical sequencing centers looking to perform similar analyses on their data.Genetics in Medicine advance online publication, 16 November 2017; doi:10.1038/gim.2017.192.

DOI10.1038/gim.2017.192
Alternate JournalGenet. Med.
PubMed ID29144510
Grant ListU01 HG006487 / HG / NHGRI NIH HHS / United States