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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 "lionessR" in publications use:'
type: software
license: MIT
title: 'lionessR: Modeling networks for individual samples using LIONESS'
version: 1.19.0
doi: 10.1101/582098
abstract: LIONESS, or Linear Interpolation to Obtain Network Estimates for Single
  Samples, can be used to reconstruct single-sample networks (https://arxiv.org/abs/1505.06440).
  This code implements the LIONESS equation in the lioness function in R to reconstruct
  single-sample networks. The default network reconstruction method we use is based
  on Pearson correlation. However, lionessR can run on any network reconstruction
  algorithms that returns a complete, weighted adjacency matrix. lionessR works for
  both unipartite and bipartite networks.
authors:
- family-names: Kuijjer
  given-names: Marieke Lydia
  email: marieke.kuijjer@ncmm.uio.no
  orcid: https://orcid.org/0000-0001-6280-3130
- family-names: Hsieh
  given-names: Ping-Han
  email: dn070017@gmail.com
  orcid: https://orcid.org/0000-0003-3054-1409
preferred-citation:
  type: unpublished
  title: 'lionessR: single-sample network reconstruction in R'
  authors:
  - family-names: Kuijjer
    given-names: Marieke Lydia
    email: marieke.kuijjer@ncmm.uio.no
    orcid: https://orcid.org/0000-0001-6280-3130
  - family-names: Quackenbush
    given-names: John
  - family-names: Glass
    given-names: Kimberly
  year: '2019'
  doi: 10.1101/582098
  notes: published on bioRxiv preprint server
  url: https://www.biorxiv.org/content/10.1101/582098v1
repository: https://bioc.r-universe.dev
repository-code: https://github.com/mararie/lionessR
url: https://github.com/mararie/lionessR
contact:
- family-names: Hsieh
  given-names: Ping-Han
  email: dn070017@gmail.com
  orcid: https://orcid.org/0000-0003-3054-1409