Sun Shanwen, Xu Lei, Zou Quan, Wang Guohua
Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, 610054 China.
School of Electronic and Communication Engineering, Shenzhen Polytechnic, Shenzhen, 518055 China.
Bioinformatics. 2021 Jun 9;37(9):1319-1321. doi: 10.1093/bioinformatics/btaa832.
Processing raw reads of RNA-sequencing (RNA-seq) data, no matter public or newly sequenced data, involves a lot of specialized tools and technical configurations that are often unfamiliar and time-consuming to learn for non-bioinformatics researchers. Here, we develop the R package BP4RNAseq, which integrates the state-of-art tools from both alignment-based and alignment-free quantification workflows. The BP4RNAseq package is a highly automated tool using an optimized pipeline to improve the sensitivity and accuracy of RNA-seq analyses. It can take only two non-technical parameters and output six formatted gene expression quantification at gene and transcript levels. The package applies to both retrospective and newly generated bulk RNA-seq data analyses and is also applicable for single-cell RNA-seq analyses. It, therefore, greatly facilitates the application of RNA-seq.
The BP4RNAseq package for R and its documentation are freely available at https://github.com/sunshanwen/BP4RNAseq.
Supplementary data are available at Bioinformatics online.
处理RNA测序(RNA-seq)数据的原始读数,无论是公共数据还是新测序的数据,都涉及许多专门的工具和技术配置,对于非生物信息学研究人员来说,这些工具和配置往往不熟悉且学习起来很耗时。在这里,我们开发了R包BP4RNAseq,它整合了基于比对和无比对定量工作流程中的先进工具。BP4RNAseq包是一个高度自动化的工具,使用优化的流程来提高RNA-seq分析的灵敏度和准确性。它只需要两个非技术参数,并在基因和转录本水平输出六种格式化的基因表达定量结果。该包适用于回顾性和新生成的批量RNA-seq数据分析,也适用于单细胞RNA-seq分析。因此,它极大地促进了RNA-seq的应用。
用于R的BP4RNAseq包及其文档可在https://github.com/sunshanwen/BP4RNAseq上免费获取。
补充数据可在《生物信息学》在线获取。