BISR-RNAseq: an efficient and scalable RNAseq analysis workflow with interactive report generation

BMC Bioinformatics

Venkat Sundar Gadepalli¹  Hatice Gulcin Ozer¹  Ayse Selen Yilmaz¹  Maciej Pietrzak¹  Amy Webb¹ 

[1] Biomedical Informatics, The Ohio State University;

关键词: RNAseq;    Transcriptome;    Workflow;    Visualization;   

DOI  :  10.1186/s12859-019-3251-1

来源: DOAJ

【 摘 要 】

Abstract Background RNA sequencing has become an increasingly affordable way to profile gene expression patterns. Here we introduce a workflow implementing several open-source softwares that can be run on a high performance computing environment. Results Developed as a tool by the Bioinformatics Shared Resource Group (BISR) at the Ohio State University, we have applied the pipeline to a few publicly available RNAseq datasets downloaded from GEO in order to demonstrate the feasibility of this workflow. Source code is available here: workflow: https://code.bmi.osumc.edu/gadepalli.3/BISR-RNAseq-ICIBM2019 and shiny: https://code.bmi.osumc.edu/gadepalli.3/BISR_RNASeq_ICIBM19. Example dataset is demonstrated here: https://dataportal.bmi.osumc.edu/RNA_Seq/. Conclusion The workflow allows for the analysis (alignment, QC, gene-wise counts generation) of raw RNAseq data and seamless integration of quality analysis and differential expression results into a configurable R shiny web application.

【 授权许可】

Unknown