Exploring the single-cell RNA-seq analysis landscape with the scRNA-tools database

single-cell
rna-seq
database
Authors

Luke Zappia

Belinda Phipson

Alicia Oshlack

Date

June 1, 2018

Links
Citation stats
Abstract

As single-cell RNA-sequencing (scRNA-seq) datasets have become more widespread the number of tools designed to analyse these data has dramatically increased. Navigating the vast sea of tools now available is becoming increasingly challenging for researchers. In order to better facilitate selection of appropriate analysis tools we have created the scRNA-tools database (www.scRNA-tools.org) to catalogue and curate analysis tools as they become available. Our database collects a range of information on each scRNA-seq analysis tool and categorises them according to the analysis tasks they perform. Exploration of this database gives insights into the areas of rapid development of analysis methods for scRNA-seq data. We see that many tools perform tasks specific to scRNA-seq analysis, particularly clustering and ordering of cells. We also find that the scRNA-seq community embraces an open-source and open-science approach, with most tools available under open-source licenses and preprints being extensively used as a means to describe methods. The scRNA-tools database provides a valuable resource for researchers embarking on scRNA-seq analysis and records the growth of the field over time.

Citation

BibTeX citation:
@article{zappia2018,
  author = {Zappia, Luke and Phipson, Belinda and Oshlack, Alicia},
  title = {Exploring the Single-Cell {RNA-seq} Analysis Landscape with
    the {scRNA-tools} Database},
  journal = {PLoS computational biology},
  volume = {14},
  number = {6},
  pages = {e1006245},
  date = {2018-06-01},
  url = {https://lazappi.id.au/publications/2018-zappia-scRNAtools/},
  doi = {10.1371/journal.pcbi.1006245},
  issn = {1553-734X, 1553-7358},
  langid = {en},
  abstract = {As single-cell RNA-sequencing (scRNA-seq) datasets have
    become more widespread the number of tools designed to analyse these
    data has dramatically increased. Navigating the vast sea of tools
    now available is becoming increasingly challenging for researchers.
    In order to better facilitate selection of appropriate analysis
    tools we have created the scRNA-tools database (www.scRNA-tools.org)
    to catalogue and curate analysis tools as they become available. Our
    database collects a range of information on each scRNA-seq analysis
    tool and categorises them according to the analysis tasks they
    perform. Exploration of this database gives insights into the areas
    of rapid development of analysis methods for scRNA-seq data. We see
    that many tools perform tasks specific to scRNA-seq analysis,
    particularly clustering and ordering of cells. We also find that the
    scRNA-seq community embraces an open-source and open-science
    approach, with most tools available under open-source licenses and
    preprints being extensively used as a means to describe methods. The
    scRNA-tools database provides a valuable resource for researchers
    embarking on scRNA-seq analysis and records the growth of the field
    over time.}
}
For attribution, please cite this work as:
Zappia, Luke, Belinda Phipson, and Alicia Oshlack. 2018. “Exploring the Single-Cell RNA-Seq Analysis Landscape with the scRNA-Tools Database.” PLoS Computational Biology 14 (June): e1006245. https://doi.org/10.1371/journal.pcbi.1006245.