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# CITATION file created with {cffr} R package
# See also: https://docs.ropensci.org/cffr/
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cff-version: 1.2.0
message: 'To cite package "CelliD" in publications use:'
type: software
license: GPL-3.0-only
title: 'CelliD: Unbiased Extraction of Single Cell gene signatures using Multiple
  Correspondence Analysis'
version: 1.13.0
doi: 10.1101/2020.07.23.215525
abstract: CelliD is a clustering-free multivariate statistical method for the robust
  extraction of per-cell gene signatures from single-cell RNA-seq. CelliD allows unbiased
  cell identity recognition across different donors, tissues-of-origin, model organisms
  and single-cell omics protocols. The package can also be used to explore functional
  pathways enrichment in single cell data.
authors:
- family-names: Cortal
  given-names: Akira
  email: akira.cortal@institutimagine.org
- family-names: Rausell
  given-names: Antonio
  email: antonio.rausell@institutimagine.org
preferred-citation:
  type: article
  title: 'Cell-ID: gene signature extraction and cell identity recognition at individual
    cell level'
  authors:
  - family-names: Cortal
    given-names: Akira
    email: akira.cortal@institutimagine.org
  - family-names: Martignetti
    given-names: Loredana
  - family-names: Six
    given-names: Emanuelle
  - family-names: Rausell
    given-names: Antonio
    email: antonio.rausell@institutimagine.org
  journal: bioRxiv
  year: '2020'
  month: '7'
  doi: 10.1101/2020.07.23.215525
repository: https://bioc.r-universe.dev
contact:
- family-names: Cortal
  given-names: Akira
  email: akira.cortal@institutimagine.org