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A Beginner’s Guide to Analysis of RNA Sequencing Data
- 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.
- Subjects :
- Data Analysis
Male
Quality Control
0301 basic medicine
Pulmonary and Respiratory Medicine
Computer science
Clinical Biochemistry
Sequencing data
computer.software_genre
03 medical and health sciences
Animals
Coining (metalworking)
Meaning (existential)
Molecular Biology
Sequence Analysis, RNA
business.industry
Gene Expression Profiling
High-Throughput Nucleotide Sequencing
Cell Biology
Term (time)
Mice, Inbred C57BL
Translational Review
030104 developmental biology
Artificial intelligence
Transcriptome
business
computer
Software
Natural language processing
Subjects
Details
- ISSN :
- 15354989 and 10441549
- Volume :
- 59
- Database :
- OpenAIRE
- Journal :
- American Journal of Respiratory Cell and Molecular Biology
- Accession number :
- edsair.doi.dedup.....ffcf659cff5797adf30035c814461549