BISR-RNAseq: an efficient and scalable RNAseq analysis workflow with interactive report generation.
BMC Bioinformatics
; 20(Suppl 24): 670, 2019 Dec 20.
Article
em En
| MEDLINE
| ID: mdl-31861980
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.Palavras-chave
Texto completo:
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Base de dados:
MEDLINE
Assunto principal:
RNA
/
Análise de Sequência de RNA
Limite:
Humans
Idioma:
En
Ano de publicação:
2019
Tipo de documento:
Article