TNER: a novel background error suppression method for mutation detection in circulating tumor DNA
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 e...
| Main Authors: | , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2018-10-01
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| Series: | BMC Bioinformatics |
| Subjects: | |
| Online Access: | http://link.springer.com/article/10.1186/s12859-018-2428-3 |
| _version_ | 1828888922126548992 |
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| author | Shibing Deng Maruja Lira Donghui Huang Kai Wang Crystal Valdez Jennifer Kinong Paul A. Rejto Jadwiga Bienkowska James Hardwick Tao Xie |
| author_facet | Shibing Deng Maruja Lira Donghui Huang Kai Wang Crystal Valdez Jennifer Kinong Paul A. Rejto Jadwiga Bienkowska James Hardwick Tao Xie |
| author_sort | Shibing Deng |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-13T12:32:11Z |
| format | Article |
| id | doaj.art-2a29b2d994f64e8d83cd250baf282277 |
| institution | Directory Open Access Journal |
| issn | 1471-2105 |
| language | English |
| last_indexed | 2024-12-13T12:32:11Z |
| publishDate | 2018-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Bioinformatics |
| spelling | doaj.art-2a29b2d994f64e8d83cd250baf2822772022-12-21T23:46:00ZengBMCBMC Bioinformatics1471-21052018-10-011911710.1186/s12859-018-2428-3TNER: a novel background error suppression method for mutation detection in circulating tumor DNAShibing Deng0Maruja Lira1Donghui Huang2Kai Wang3Crystal Valdez4Jennifer Kinong5Paul A. Rejto6Jadwiga Bienkowska7James Hardwick8Tao Xie9Pfizer Early Clinical Development BiostatisticsPfizer Oncology R & DPfizer Oncology R & DPfizer Oncology R & DPfizer Oncology R & DPfizer Oncology R & DPfizer Oncology R & DPfizer Oncology R & DPfizer Oncology R & DPfizer Oncology R & DAbstract 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.http://link.springer.com/article/10.1186/s12859-018-2428-3ctDNANext-generation sequencingVariant callingError suppressionSingle-nucleotide variant |
| spellingShingle | Shibing Deng Maruja Lira Donghui Huang Kai Wang Crystal Valdez Jennifer Kinong Paul A. Rejto Jadwiga Bienkowska James Hardwick Tao Xie TNER: a novel background error suppression method for mutation detection in circulating tumor DNA BMC Bioinformatics ctDNA Next-generation sequencing Variant calling Error suppression Single-nucleotide variant |
| title | TNER: a novel background error suppression method for mutation detection in circulating tumor DNA |
| title_full | TNER: a novel background error suppression method for mutation detection in circulating tumor DNA |
| title_fullStr | TNER: a novel background error suppression method for mutation detection in circulating tumor DNA |
| title_full_unstemmed | TNER: a novel background error suppression method for mutation detection in circulating tumor DNA |
| title_short | TNER: a novel background error suppression method for mutation detection in circulating tumor DNA |
| title_sort | tner a novel background error suppression method for mutation detection in circulating tumor dna |
| topic | ctDNA Next-generation sequencing Variant calling Error suppression Single-nucleotide variant |
| url | http://link.springer.com/article/10.1186/s12859-018-2428-3 |
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