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

doi:10.1165/rcmb.2017-0430TR

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 journal › Review article › peer-review

100 Scopus citations

Abstract

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 language	English (US)
Pages (from-to)	145-157
Number of pages	13
Journal	American journal of respiratory cell and molecular biology
Volume	59
Issue number	2
DOIs	https://doi.org/10.1165/rcmb.2017-0430TR
State	Published - Aug 2018

Funding

*These authors contributed equally to this work. ‡These authors contributed equally to this work. Supported by National Institutes of Health (NIH)/National Institute of Diabetes and Digestive and Kidney Diseases grant T32DK077662 (S.F.C.), NIH/National Heart, Lung, and Blood Institute (NHLBI) grants HL128194 and HL071643 (K.M.R.) and HL125940 (A.B.), matching funds from the Thoracic Surgery Foundation (A.B.) and the American Society of Transplant Surgeons Foundation (S.F.C.), and U.S. Department of Defense grant W81XWH-15-1-0214 (E.T.B.). The Winter laboratory is funded by the Northwestern Memorial Foundation Dixon Award, the Arthritis National Research Foundation, and the American Lung Association.

Keywords

Bioinformatics
Data analysis
RNA sequencing
Transcriptomics

ASJC Scopus subject areas

Molecular Biology
Pulmonary and Respiratory Medicine
Clinical Biochemistry
Cell Biology

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abstract = "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.",

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A beginner’s guide to analysis of RNA sequencing data

Abstract

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Keywords

ASJC Scopus subject areas

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