Journal
BIOINFORMATICS
Volume 29, Issue 14, Pages 1809-1810Publisher
OXFORD UNIV PRESS
DOI: 10.1093/bioinformatics/btt268
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Funding
- Berlin Institute for Medical Systems Biology at the MDC
- Federal Ministry for Education and Research (BMBF)
- Senate of Berlin, Berlin, Germany [0315362A]
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Direct comparisons of assembled short-read stacks are one way to identify single-nucleotide variants. Single-nucleotide variant detection is especially challenging across samples with different read depths (e. g. RNA-Seq) and high-background levels (e. g. selection experiments). We present ACCUSA2 to identify variant positions where nucleotide frequency spectra differ between two samples. To this end, ACCUSA2 integrates quality scores for base calling and read mapping into a common framework. Our benchmarks demonstrate that ACCUSA2 is superior to a state-of-the-art SNV caller in situations of diverging read depths and reliably detects subtle differences among sample nucleotide frequency spectra. Additionally, we show that ACCUSA2 is fast and robust against base quality score deviations.
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