|
1
|
Zhou W, Chen T, Zhao H, Eterovic AK, Meric-Bernstam F, Mills GB, Chen K. Bias from removing read duplication in ultra-deep sequencing experiments. ACTA ACUST UNITED AC 2014; 30:1073-1080. [PMID: 24389657 DOI: 10.1093/bioinformatics/btt771] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/17/2013] [Accepted: 12/25/2013] [Indexed: 12/30/2022]
Abstract
MOTIVATION Identifying subclonal mutations and their implications requires accurate estimation of mutant allele fractions from possibly duplicated sequencing reads. Removing duplicate reads assumes that polymerase chain reaction amplification from library constructions is the primary source. The alternative-sampling coincidence from DNA fragmentation-has not been systematically investigated. RESULTS With sufficiently high-sequencing depth, sampling-induced read duplication is non-negligible, and removing duplicate reads can overcorrect read counts, causing systemic biases in variant allele fraction and copy number variation estimations. Minimal overcorrection occurs when duplicate reads are identified accounting for their mate reads, inserts are of a variety of lengths and samples are sequenced in separate batches. We investigate sampling-induced read duplication in deep sequencing data with 500× to 2000× duplicates-removed sequence coverage. We provide a quantitative solution to overcorrection and guidance for effective designs of deep sequencing platforms that facilitate accurate estimation of variant allele fraction and copy number variation. AVAILABILITY AND IMPLEMENTATION A Python implementation is freely available at https://bitbucket.org/wanding/duprecover/overview CONTACT: : wzhou1@mdanderson.org, kchen3@mdanderson.org Supplementary information: Supplementary data are available at Bioinformatics online.
Collapse
Affiliation(s)
- Wanding Zhou
- Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA
| | - Tenghui Chen
- Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA
| | - Hao Zhao
- Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA
| | - Agda Karina Eterovic
- Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA
| | - Funda Meric-Bernstam
- Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA
| | - Gordon B Mills
- Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA
| | - Ken Chen
- Department of Bioinformatics and Computational Biology, Department of Systems Biology, Institute of Personalized Cancer Therapy and Department of Investigational Cancer Therapy, The University of Texas MD Anderson Cancer Center, Houston TX 77030, USA
| |
Collapse
|