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 Publication2018
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
Corporate AuthorsNHGRI Clinical Sequencing Exploratory Research (CSER) Consortium
JournalGenet Med
Volume20
Issue8
Pagination855-866
Date Published2018 08
ISSN1530-0366
KeywordsBase Sequence, Chromosome Mapping, Exome, Genome, Human, High-Throughput Nucleotide Sequencing, Humans, Sequence Analysis, DNA, Software, Whole Exome Sequencing, Whole Genome Sequencing
Abstract

PURPOSE: As 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.

METHODS: To 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.

RESULTS: This 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.

CONCLUSION: This report provides a process road map for clinical sequencing centers looking to perform similar analyses on their data.

DOI10.1038/gim.2017.192
Alternate JournalGenet Med
PubMed ID29144510
PubMed Central IDPMC6456263
Grant ListU01 HG007301 / HG / NHGRI NIH HHS / United States
U41 HG006834 / HG / NHGRI NIH HHS / United States
ZIA HG200359 / ImNIH / Intramural NIH HHS / United States
U19 HD077632 / HD / NICHD NIH HHS / United States
U01 HG006485 / HG / NHGRI NIH HHS / United States
Z99 HG999999 / ImNIH / Intramural NIH HHS / United States
UM1 HG007292 / HG / NHGRI NIH HHS / United States
U01 HG006500 / HG / NHGRI NIH HHS / United States
UM1 HG008898 / HG / NHGRI NIH HHS / United States
UM1 HG007301 / HG / NHGRI NIH HHS / United States
U01 HG007307 / HG / NHGRI NIH HHS / United States
U01 HG007292 / HG / NHGRI NIH HHS / United States
R01 DA030976 / DA / NIDA NIH HHS / United States
U01 HG006507 / HG / NHGRI NIH HHS / United States
U54 HG003273 / HG / NHGRI NIH HHS / United States
U01 HG006487 / HG / NHGRI NIH HHS / United States
U01 HG006492 / HG / NHGRI NIH HHS / United States
ZIA HG200359-08 / ImNIH / Intramural NIH HHS / United States

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