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# CITATION.cff file created with {cffr} R package
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cff-version: 1.2.0
message: 'To cite package "exposomeSC" in publications use:'
type: software
license: Artistic-2.0
title: 'exposomeSC: Single-Cell Exposome-Wide Association Studies with Cross-Omic
  Network Inference'
version: 0.99.1
doi: 10.32614/CRAN.package.exposomeSC
abstract: A framework for cell-type-specific exposome-wide association studies (sc-ExWAS)
  that bridges donor-level environmental exposures with single-cell resolution gene
  expression. The package extends SingleCellExperiment to store exposure measurements
  alongside transcriptomic data, and implements donor-level raw-count pseudobulk inference
  to avoid cellular pseudoreplication (Squair et al. 2021 <https://doi.org/10.1038/s41467-021-25960-2>).
  The default workflow uses robust edgeR quasi-likelihood models, exposure-independent
  expression-support filtering, complete-transcriptome offsets, design-rank diagnostics,
  and global multiplicity correction. Additional modules support dose-response modelling,
  exposure mixtures, cross-cohort synthesis, and cell-level gene-protein coupling.
  Exploratory decomposition and mediation utilities report model-based associations;
  they do not by themselves identify causal effects.
authors:
- family-names: Gao
  given-names: Cuiwei
  email: 48gaocuiwei@gmail.com
repository: https://biocstaging.r-universe.dev
repository-code: https://github.com/CuiweiG/exposomeSC
commit: 349221639c2f7d246a61c527939db1e69c58d5d4
url: https://github.com/CuiweiG/exposomeSC
date-released: '2026-09-23'
contact:
- family-names: Gao
  given-names: Cuiwei
  email: 48gaocuiwei@gmail.com