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BMC Bioinformatics. 2018 Oct 20;19(1):387. doi: 10.1186/s12859-018-2428-3.

TNER: a novel background error suppression method for mutation detection in circulating tumor DNA.

Author information

1
Pfizer Early Clinical Development Biostatistics, Cambridge, UK.
2
Pfizer Oncology R & D, San Diego, CA, USA.
3
Pfizer Oncology R & D, San Diego, CA, USA. xietao2000@gmail.com.

Abstract

BACKGROUND:

Ultra-deep next-generation sequencing of circulating tumor DNA (ctDNA) holds great promise as a tool for the early detection of cancer and for monitoring disease progression and therapeutic responses. However, the low abundance of ctDNA in the bloodstream coupled with technical errors introduced during library construction and sequencing complicates mutation detection.

RESULTS:

To achieve high accuracy of variant calling via better distinguishing low-frequency ctDNA mutations from background errors, we introduce TNER (Tri-Nucleotide Error Reducer), a novel background error suppression method that provides a robust estimation of background noise to reduce sequencing errors. The results on both simulated data and real data from healthy subjects demonstrate that the proposed algorithm consistently outperforms a current, state-of-the-art, position-specific error polishing model, particularly when the sample size of healthy subjects is small.

CONCLUSIONS:

TNER significantly enhances the specificity of downstream ctDNA mutation detection without sacrificing sensitivity. The tool is publicly available at https://github.com/ctDNA/TNER .

KEYWORDS:

Error suppression; Next-generation sequencing; Single-nucleotide variant; Variant calling; ctDNA

PMID:
30342468
PMCID:
PMC6195972
DOI:
10.1186/s12859-018-2428-3
[Indexed for MEDLINE]
Free PMC Article

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