title: Single-Cell Transcriptomics Bioinformatics and Computational Challenges.
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.
authors.affiliation: Epidemiology Program, University of Hawaii Cancer Center Honolulu, HI, USA.
authors.forename: Olivier B
authors.initials: OB
authors.lastname: Poirion
authors.affiliation: Epidemiology Program, University of Hawaii Cancer CenterHonolulu, HI, USA; Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at ManoaHonolulu, HI, USA.
authors.forename: Xun
authors.initials: X
authors.lastname: Zhu
authors.affiliation: Epidemiology Program, University of Hawaii Cancer CenterHonolulu, HI, USA; Molecular Biosciences and Bioengineering Graduate Program, University of Hawaii at ManoaHonolulu, HI, USA.
authors.forename: Travers
authors.initials: T
authors.lastname: Ching
authors.affiliation: Epidemiology Program, University of Hawaii Cancer Center Honolulu, HI, USA.
authors.forename: Lana
authors.initials: L
authors.lastname: Garmire
keywords: bioinformatics; heterogeneity; microevolution; single-cell analysis; single-cell genomics