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A Beginner’s Guide to Analysis of RNA Sequencing Data

Authors :
Clarissa M. Koch
Ankit Bharat
Karen M. Ridge
Mahzad Akbarpour
Deborah R. Winter
Elizabeth T. Bartom
Stephen Chiu
Source :
American Journal of Respiratory Cell and Molecular Biology. 59:145-157
Publication Year :
2018
Publisher :
American Thoracic Society, 2018.

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.

Details

ISSN :
15354989 and 10441549
Volume :
59
Database :
OpenAIRE
Journal :
American Journal of Respiratory Cell and Molecular Biology
Accession number :
edsair.doi.dedup.....ffcf659cff5797adf30035c814461549