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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: 0.99.5
abstract: Causal ASCEND (Ancestral Scalable Causal discovEry via iNherited Descent)
  infers ancestral (cause-before-effect) 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://bioc.r-universe.dev
repository-code: https://github.com/SparkAILab/causalASCEND
commit: 9104c90774ead6bbda65320363ca5ef0c136e922
url: https://github.com/SparkAILab/causalASCEND
date-released: '2026-11-06'
contact:
- family-names: Asiedu
  given-names: Stephen
  email: stephen.asiedu@kcl.ac.uk
  orcid: https://orcid.org/0009-0005-8885-5381