QoRTs: a comprehensive toolset for quality control and data processing of RNA-Seq experiments

BMC Bioinformatics

Software

Stephen W. Hartley¹  James C. Mullikin¹ 

[1] Comparative Genomics Analysis Unit, Cancer Genetics and Comparative Genomics Branch, National Human Genome Research Institute, National Institutes of Health, 20892, Bethesda, MD, USA;

关键词: Quality Control;    RNA-Seq;    Next-generation sequencing;    Differential expression;    Differential transcript regulation;    Differential splicing;   

DOI  :  10.1186/s12859-015-0670-5

 received in 2015-05-26, accepted in 2015-07-09,  发布年份 2015

来源: Springer

【 摘 要 】

BackgroundHigh-throughput next-generation RNA sequencing has matured into a viable and powerful method for detecting variations in transcript expression and regulation. Proactive quality control is of critical importance as unanticipated biases, artifacts, or errors can potentially drive false associations and lead to flawed results.ResultsWe have developed the Quality of RNA-Seq Toolset, or QoRTs, a comprehensive, multifunction toolset that assists in quality control and data processing of high-throughput RNA sequencing data.ConclusionsQoRTs generates an unmatched variety of quality control metrics, and can provide cross-comparisons of replicates contrasted by batch, biological sample, or experimental condition, revealing any outliers and/or systematic issues that could drive false associations or otherwise compromise downstream analyses. In addition, QoRTs simultaneously replaces the functionality of numerous other data-processing tools, and can quickly and efficiently generate quality control metrics, coverage counts (for genes, exons, and known/novel splice-junctions), and browser tracks. These functions can all be carried out as part of a single unified data-processing/quality control run, greatly reducing both the complexity and the total runtime of the analysis pipeline. The software, source code, and documentation are available online at http://hartleys.github.io/QoRTs.

【 授权许可】

CC BY   
© Hartley and Mullikin. 2015