A beginner’s guide to analysis of RNA sequencing data

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

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

73 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)145-157
Number of pages13
JournalAmerican journal of respiratory cell and molecular biology
Issue number2
StatePublished - Aug 2018


  • Bioinformatics
  • Data analysis
  • RNA sequencing
  • Transcriptomics

ASJC Scopus subject areas

  • Molecular Biology
  • Pulmonary and Respiratory Medicine
  • Clinical Biochemistry
  • Cell Biology


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