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.
Bioinformatics. 2013 Jul 15;29(14):1809-10. doi: 10.1093/bioinformatics/btt268. Epub 2013 May 16.
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.
ACCUSA2 is available free of charge to academic users and may be obtained from https://bbc.mdc-berlin.de/software.
christoph.dieterich@mdc-berlin.de
Supplementary data are available at Bioinformatics online.
直接比较已组装的短读序列是识别单核苷酸变异的一种方法。在具有不同读深（例如 RNA-Seq）和高背景水平（例如选择实验）的样本中，单核苷酸变异检测尤其具有挑战性。我们提出了 ACCUSA2 来识别两个样本中核苷酸频率谱差异的变异位置。为此，ACCUSA2 将碱基调用和读映射的质量评分集成到一个通用框架中。我们的基准测试表明，在读取深度不同的情况下，ACCUSA2 优于最先进的单核苷酸变异 caller，并可靠地检测到样本核苷酸频率谱之间的细微差异。此外，我们还表明，ACCUSA2 对碱基质量评分偏差具有快速和稳健的特性。
ACCUSA2 可供学术用户免费使用，并可从 https://bbc.mdc-berlin.de/software 获得。
christoph.dieterich@mdc-berlin.de
补充数据可在 Bioinformatics 在线获得。
