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A Beginner's Guide to Analysis of RNA Sequencing Data

Koch, Clarissa M.; Chiu, Stephen F.; Akbarpour, Mahzad; Bharat, Ankit; Ridge, Karen M.; Bartom, Elizabeth T.; Winter, Deborah R.

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PMID: 29624415 PMCID: PMC6096346


Since the first publications coining the term RNA-seq (RNA sequencing) appeared in 2008, the number of publications containing RNA-seq data has grown exponentially, hitting an all-time high of 2,808 publications in 2016 (PubMed). With this wealth of RNA-seq data being generated, it is a challenge to extract maximal meaning from these datasets, and without the appropriate skills and background, there is risk of misinterpretation of these data. However, a general understanding of the principles underlying each step of RNA-seq data analysis allows investigators without a background in programming and bioinformatics to critically analyze their own datasets as well as published data. Our goals in the present review are to break down the steps of a typical RNA-seq analysis and to highlight the pitfalls and checkpoints along the way that are vital for bench scientists and biomedical researchers performing experiments that use RNA-seq.

Automatic Tags

Male; transcriptomics; Mice, Inbred C57BL; Software; Sequence Analysis, RNA; Transcriptome; Gene Expression Profiling; High-Throughput Nucleotide Sequencing; bioinformatics; Quality Control; RNA sequencing

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