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bioRxiv · 10.1101/641324

RNASeqR: an R package for automated two-group RNA-Seq analysis workflow

Chao, K.-H.·Hsiao, Y.-W.·Lee, Y.-F.·Lee, C.-Y.·Lai, L.-C.·Tsai, M.-H.·Lu, T.-P.·Chuang, E. Y.
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Abstract

RNA-Seq analysis has revolutionized researchers understanding of the transcriptome in biological research. Assessing the differences in transcriptomic profiles between tissue samples or patient groups enables researchers to explore the underlying biological impact of transcription. RNA-Seq analysis requires multiple processing steps and huge computational capabilities. There are many well-developed R packages for individual steps; however, there are few R/Bioconductor packages that integrate existing software tools into a comprehensive RNA-Seq analysis and provide fundamental end-to-end results in pure R environment so that researchers can quickly and easily get fundamental information in big sequencing data. To address this need, we have developed the open source R/Bioconductor package, RNASeqR. It allows users to run an automated RNA-Seq analysis with only six steps, producing essential tabular and graphical results for further biological interpretation. The features of RNASeqR include: six-step analysis, comprehensive visualization, background execution version, and the integration of both R and command-line software. RNASeqR provides fast, light-weight, and easy-to-run RNA-Seq analysis pipeline in pure R environment. It allows users to efficiently utilize popular software tools, including both R/Bioconductor and command-line tools, without predefining the resources or environments. RNASeqR is freely available for Linux and macOS operating systems from Bioconductor (https://bioconductor.org/packages/release/bioc/html/RNASeqR.html).

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Chao, K.-H., Hsiao, Y.-W., Lee, Y.-F., Lee, C.-Y., Lai, L.-C., Tsai, M.-H., Lu, T.-P., Chuang, E. Y.. 2019-05-27. RNASeqR: an R package for automated two-group RNA-Seq analysis workflow. https://doi.org/10.1101/641324

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