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


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.

SUBMITTER: Gadepalli VS 

PROVIDER: S-EPMC6923898 | biostudies-literature | 2019 Dec

REPOSITORIES: biostudies-literature

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

Gadepalli Venkat Sundar VS   Ozer Hatice Gulcin HG   Yilmaz Ayse Selen AS   Pietrzak Maciej M   Webb Amy A  

BMC bioinformatics 20191220 Suppl 24


<h4>Background</h4>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.<h4>Results</h4>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 th  ...[more]

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