Analysis of error profiles in deep next-generation sequencing data

Analysis of error profiles in deep next-generation sequencing data

Abstract Background Sequencing errors are key confounding factors for detecting low-frequency genetic variants that are important for cancer molecular diagnosis, treatment, and surveillance using deep next-generation sequencing (NGS). However, there is a lack of comprehensive understanding of errors...

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Bibliographic Details
Main Authors: Xiaotu Ma, Ying Shao, Liqing Tian, Diane A. Flasch, Heather L. Mulder, Michael N. Edmonson, Yu Liu, Xiang Chen, Scott Newman, Joy Nakitandwe, Yongjin Li, Benshang Li, Shuhong Shen, Zhaoming Wang, Sheila Shurtleff, Leslie L. Robison, Shawn Levy, John Easton, Jinghui Zhang
Format: Article
Language:English
Published: BMC 2019-03-01
Series:Genome Biology
Subjects:
Deep sequencing
Error rate
Substitution
Subclonal
Detection
Hotspot mutation
Online Access:http://link.springer.com/article/10.1186/s13059-019-1659-6

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