ACCUSA2: Multi-purpose SNV calling enhanced by probabilistic integration of quality scores

Item Type:	Article
Title:	ACCUSA2: Multi-purpose SNV calling enhanced by probabilistic integration of quality scores
Creators Name:	Piechotta, M. and Dieterich, C.
Abstract:	SUMMARY: Direct comparisons of assembled short read stacks are one way to identify Single Nucleotide Variants (SNVs). SNV 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 SNP 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. Availability: ACCUSA2 is available free of charge to academic users and may be obtained from https://bbc.mdc-berlin.de/software.
Keywords:	Genetic Variation, High-Throughput Nucleotide Sequencing, Probability, Single Nucleotide Polymorphism, Software
Source:	Bioinformatics
ISSN:	1367-4803
Publisher:	Oxford University Press
Volume:	29
Number:	14
Page Range:	1809-1810
Date:	15 July 2013
Official Publication:	https://doi.org/10.1093/bioinformatics/btt268
PubMed:	View item in PubMed

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