title: ACCUSA2: multi-purpose SNV calling enhanced by probabilistic integration of quality scores.
abstract: CONCLUSIONS
  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.
  
  
  BACKGROUND
  ACCUSA2 is available free of charge to academic users and may be obtained from https://bbc.mdc-berlin.de/software.
  
  
  BACKGROUND
  christoph.dieterich@mdc-berlin.de
  
  
  BACKGROUND
  Supplementary data are available at Bioinformatics online.
authors.affiliation: Bioinformatics in Quantitative Biology, The Berlin Institute for Medical Systems Biology at the Max Delbrück Center for Molecular Medicine, Robert-Rössle-Strasse 10, 13125 Berlin-Buch, Germany.
authors.forename: Michael
authors.initials: M
authors.lastname: Piechotta
authors.forename: Christoph
authors.initials: C
authors.lastname: Dieterich
mesh_terms: D014644:Genetic Variation; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods* / Q000592:standards; D020641:Polymorphism, Single Nucleotide; D011336:Probability; D012984:Software