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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 "SPONGE" in publications use:'
type: software
title: 'SPONGE: Sparse Partial Correlations On Gene Expression'
version: 1.27.0
doi: 10.1093/bioinformatics/btz314
identifiers:
- type: doi
  value: 10.32614/CRAN.package.SPONGE
abstract: 'This package provides methods to efficiently detect competitive endogeneous
  RNA interactions between two genes. Such interactions are mediated by one or several
  miRNAs such that both gene and miRNA expression data for a larger number of samples
  is needed as input. The SPONGE package now also includes spongEffects: ceRNA modules
  offer patient-specific insights into the miRNA regulatory landscape.'
authors:
- family-names: List
  given-names: Markus
  email: markus.list@tum.de
  orcid: https://orcid.org/0000-0002-0941-4168
- family-names: Hoffmann
  given-names: Markus
  email: markus.daniel.hoffmann@tum.de
  orcid: https://orcid.org/0000-0002-1920-288X
preferred-citation:
  type: article
  title: Large-scale inference of competing endogenous RNA networks with sparse partial
    correlation
  authors:
  - family-names: List
    given-names: Markus
    email: markus.list@tum.de
    orcid: https://orcid.org/0000-0002-0941-4168
  - family-names: Amirabad
    given-names: Azim Dehghani
  - family-names: Kostka
    given-names: Dennis
  - family-names: Schulz
    given-names: Marcle H.
  year: '2019'
  doi: 10.1093/bioinformatics/btz314
  abstract: MicroRNAs (miRNAs) are important non-coding post-transcriptional regulators
    that are involved in many biological processes and human diseases. Individual
    miRNAs may regulate hundreds of genes, giving rise to a complex gene regulatory
    network in which transcripts carrying miRNA binding sites act as competing endogenous
    RNAs (ceRNAs). Several methods for the analysis of ceRNA interactions exist, but
    these do often not adjust for statistical confounders or address the problem that
    more than one miRNA interacts with a target transcript. We present SPONGE, a method
    for the fast construction of ceRNA networks. SPONGE uses ?multiple sensitivity
    correlation?, a newly defined measure for which we can estimate a distribution
    under a null hypothesis. SPONGE can accurately quantify the contribution of multiple
    miRNAs to a ceRNA interaction with a probabilistic model that addresses previously
    neglected confounding factors and allows fast P-value calculation, thus outperforming
    existing approaches. We applied SPONGE to paired miRNA and gene expression data
    from The Cancer Genome Atlas for studying global effects of miRNA-mediated cross-talk.
    Our results highlight already established and novel protein-coding and non-coding
    ceRNAs which could serve as biomarkers in cancer.
  url: https://doi.org/10.1093/bioinformatics/btz314
  journal: Bioinformatics
repository: https://bioc.r-universe.dev
commit: 485926e00967ef0232badaee83f6a33a0ed807fc
contact:
- family-names: List
  given-names: Markus
  email: markus.list@tum.de
  orcid: https://orcid.org/0000-0002-0941-4168