LFMD: detecting low-frequency mutations in high-depth genome sequencing data without molecular tags
Pak C Sham
Posted 24 Apr 2019
bioRxiv DOI: 10.1101/617381
Posted 24 Apr 2019
As next-generation sequencing (NGS) and liquid biopsy become more prevalent in research and in the clinic, there is an increasing need for better methods to reduce cost and improve sensitivity and specificity of low-frequency mutation detection (where the Alternative Allele Frequency, or AAF, is less than 1%). Here we propose a likelihood-based approach, called Low-Frequency Mutation Detector (LFMD), which combines the advantages of duplex sequencing (DS) and the bottleneck sequencing system (BotSeqS) to maximize the utilization of duplicate reads. Compared with the existing state-of-the-art methods, DS, Du Novo, UMI-tools, and Unified Consensus Maker, our method achieves higher sensitivity, higher specificity (< 4 * 10^-10 errors per base sequenced) and lower cost (reduced by ~70% at best) without involving additional experimental steps, customized adapters or molecular tags. LFMD is useful in areas where high precision is required, such as drug resistance prediction and cancer screening. As an example of LFMD's applications, mitochondrial heterogeneity analysis of 28 human brain samples across different stages of Alzheimer's Disease (AD) showed that the canonical oxidative damage related mutations, C:G>A:T, are significantly increased in the mid-stage group. This is consistent with the Mitochondrial Free Radical Theory of Aging, suggesting that AD may be linked to the aging of brain cells induced by oxidative damage.
- Downloaded 1,148 times
- Download rankings, all-time:
- Site-wide: 21,702
- In bioinformatics: 2,475
- Year to date:
- Site-wide: 56,484
- Since beginning of last month:
- Site-wide: 125,589
Downloads over time
Distribution of downloads per paper, site-wide
- 27 Nov 2020: The website and API now include results pulled from medRxiv as well as bioRxiv.
- 18 Dec 2019: We're pleased to announce PanLingua, a new tool that enables you to search for machine-translated bioRxiv preprints using more than 100 different languages.
- 21 May 2019: PLOS Biology has published a community page about Rxivist.org and its design.
- 10 May 2019: The paper analyzing the Rxivist dataset has been published at eLife.
- 1 Mar 2019: We now have summary statistics about bioRxiv downloads and submissions.
- 8 Feb 2019: Data from Altmetric is now available on the Rxivist details page for every preprint. Look for the "donut" under the download metrics.
- 30 Jan 2019: preLights has featured the Rxivist preprint and written about our findings.
- 22 Jan 2019: Nature just published an article about Rxivist and our data.
- 13 Jan 2019: The Rxivist preprint is live!