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# CITATION.cff 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 "causalASCEND" in publications use:'
type: software
license: GPL-3.0-only
title: 'causalASCEND: Scalable Two-Tier Causal Discovery for Multi-Omic Data'
version: 0.99.0
abstract: Causal ASCEND (Ancestral Scalable Causal discovEry via iNherited Descent)
  infers ancestral relations among downstream molecular variables, such as gene expression,
  when a layer of upstream variables, such as genotypes or methylation sites, is known
  to precede them. Each conditional independence test conditions only on a small,
  iteratively refined set of nearest ancestors instead of the whole upstream layer,
  so the number of tests grows polynomially with the number of variables. The package
  accepts matrices, SummarizedExperiment objects or a MultiAssayExperiment, and returns
  the ancestral relations with the rule and evidence behind each one.
authors:
- family-names: Asiedu
  given-names: Stephen
  email: stephen.asiedu@kcl.ac.uk
  orcid: https://orcid.org/0009-0005-8885-5381
- family-names: Watson
  given-names: David
  email: david.watson@kcl.ac.uk
repository: https://biocstaging.r-universe.dev
repository-code: https://github.com/SparkAILab/causalASCEND
commit: c780ecd145e2db60fd9a57f5525bd1ca801a90b0
url: https://github.com/SparkAILab/causalASCEND
date-released: '2026-10-14'
contact:
- family-names: Asiedu
  given-names: Stephen
  email: stephen.asiedu@kcl.ac.uk
  orcid: https://orcid.org/0009-0005-8885-5381