Accurate single nucleotide variant detection in viral populations by combining probabilistic clustering with a statistical test of strand bias

@inproceedings{McElroy2012AccurateSN,
  title={Accurate single nucleotide variant detection in viral populations by combining probabilistic clustering with a statistical test of strand bias},
  author={Kerensa McElroy and Osvaldo Zagordi and Rowena A. Bull and Fabio Luciani and Niko Beerenwinkel},
  booktitle={BMC Genomics},
  year={2012}
}
BackgroundDeep sequencing is a powerful tool for assessing viral genetic diversity. Such experiments harness the high coverage afforded by next generation sequencing protocols by treating sequencing reads as a population sample. Distinguishing true single nucleotide variants (SNVs) from sequencing errors remains challenging, however. Current protocols are characterised by high false positive rates, with results requiring time consuming manual checking.ResultsBy statistical modelling, we show… CONTINUE READING

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