RSeQC: quality control of RNA-seq experiments
Baylor College of Medicine · State Key Laboratory of Digital Medical Engineering · +1 more institution
Abstract
MOTIVATION: RNA-seq has been extensively used for transcriptome study. Quality control (QC) is critical to ensure that RNA-seq data are of high quality and suitable for subsequent analyses. However, QC is a time-consuming and complex task, due to the massive size and versatile nature of RNA-seq data. Therefore, a convenient and comprehensive QC tool to assess RNA-seq quality is sorely needed. RESULTS: We developed the RSeQC package to comprehensively evaluate different aspects of RNA-seq experiments, such as sequence quality, GC bias, polymerase chain reaction bias, nucleotide composition bias, sequencing depth, strand specificity, coverage uniformity and read distribution over the genome structure. RSeQC…
Citation impact
- FWCI
- 18.94
- Percentile
- 100%
- References
- 10
Authors
3- LWLiguo WangCorresponding
Baylor College of Medicine, State Key Laboratory of Digital Medical Engineering, Southeast University
- SWShengqin Wang
Baylor College of Medicine, State Key Laboratory of Digital Medical Engineering, Southeast University
- WLWei Li
Baylor College of Medicine, State Key Laboratory of Digital Medical Engineering, Southeast University
Topics & keywords
- Python (programming language)
- Computer science
- Scripting language
- RNA-Seq
- RNA
- Source code
- Computational biology
- Data mining