Evaluating the performance of low-frequency variant calling tools for the detection of variants from short-read deep sequencing data
Abstract Detection of low-frequency variants with high accuracy plays an important role in biomedical research and clinical practice. However, it is challenging to do so with next-generation sequencing (NGS) approaches due to the high error rates of NGS. To accurately distinguish low-level true vari...
Main Authors: | , , , , , |
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Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2023-11-01
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Series: | Scientific Reports |
Online Access: | https://doi.org/10.1038/s41598-023-47135-3 |