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Genome Biol. 2012 May 23;13(5):R34. doi: 10.1186/gb-2012-13-5-r34.

A new approach for detecting low-level mutations in next-generation sequence data.

Author information

  • 1Department of Evolutionary Genetics, Max Planck Institute for Evolutionary Anthropology, D04103, Leipzig, Germany. mingkun_li@eva.mpg.de

Abstract

We propose a new method that incorporates population re-sequencing data, distribution of reads, and strand bias in detecting low-level mutations. The method can accurately identify low-level mutations down to a level of 2.3%, with an average coverage of 500×, and with a false discovery rate of less than 1%. In addition, we also discuss other problems in detecting low-level mutations, including chimeric reads and sample cross-contamination, and provide possible solutions to them.

PMID:
22621726
[PubMed - indexed for MEDLINE]
PMCID:
PMC3446287
Free PMC Article
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