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PMID: 27708664 Published · epublish English Review Journal Article

Single-Cell Transcriptomics Bioinformatics and Computational Challenges.

Frontiers in genetics ·Vol. 7 ·2016-00-00 ·Pages 163

Poirion OB, Zhu X, Ching T, Garmire L

Abstract

The emerging single-cell RNA-Seq (scRNA-Seq) technology holds the promise to revolutionize our understanding of diseases and associated biological processes at an unprecedented resolution. It opens the door to reveal intercellular heterogeneity and has been employed to a variety of applications, ranging from characterizing cancer cells subpopulations to elucidating tumor resistance mechanisms. Parallel to improving experimental protocols to deal with technological issues, deriving new analytical methods to interpret the complexity in scRNA-Seq data is just as challenging. Here, we review current state-of-the-art bioinformatics tools and methods for scRNA-Seq analysis, as well as addressing some critical analytical challenges that the field faces.

Keywords
bioinformatics heterogeneity microevolution single-cell analysis single-cell genomics
Authors & Affiliations
4 authors, click to expand affiliations / ORCID
Poirion Olivier B
Epidemiology Program, University of Hawaii Cancer Center Honolulu, HI, USA.
Zhu Xun
Epidemiology Program, University of Hawaii Cancer CenterHonolulu, HI, USA; Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at ManoaHonolulu, HI, USA.
Ching Travers
Epidemiology Program, University of Hawaii Cancer CenterHonolulu, HI, USA; Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at ManoaHonolulu, HI, USA.
Garmire Lana
Epidemiology Program, University of Hawaii Cancer Center Honolulu, HI, USA.
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Article Info
Journal
Frontiers in genetics
Abbr.
Front Genet
ISSN
1664-8021
DOI
10.3389/fgene.2016.00163
Published
2016-00-00
Epub
2016-00-21
Pages
163
Language
English
Region
Switzerland
NLM ID
101560621
PMCID
PMC5030210
Grants
NIEHS NIH HHS · K01 ES025434 · United States
NIGMS NIH HHS · P20 GM103457 · United States
NICHD NIH HHS · R01 HD084633 · United States
NLM NIH HHS · R01 LM012373 · United States
Corrections
CommentIn
PMID: 28682345
External Links
PubMed source DOI: 10.3389/fgene.2016.00163 PMC Full Text View journal details
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