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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 "scECODA" in publications use:'
type: software
license: GPL-3.0-only
title: 'scECODA: Single-Cell Exploratory Compositional Data Analysis'
version: 1.1.5
doi: 10.32614/CRAN.package.scECODA
abstract: The scECODA R package provides a complete workflow for the analysis and
  visualization of compositional data, primarily focusing on cell type proportions
  derived from single-cell data. It implements specialized methods, such as the Centered
  Log-Ratio (CLR) transformation, to properly analyze proportional data while avoiding
  the biases introduced by the compositional constraint. The package encapsulates
  data management, transformation, and analysis into a single SummarizedExperiment
  object, offering downstream tools for dimensionality reduction via PCA, calculating
  critical metrics like the Adjusted Rand Index (ARI) and Modularity to quantify sample
  grouping quality, and generating high-quality visualizations like heatmaps and scatter
  plots.
authors:
- family-names: Halter
  given-names: Christian
  email: scecoda.dev@gmail.com
  orcid: https://orcid.org/0009-0009-5479-2246
- family-names: Andreatta
  given-names: Massimo
  email: Massimo.Andreatta@unige.ch
  orcid: https://orcid.org/0000-0002-8036-2647
- family-names: Carmona
  given-names: Santiago
  email: Santiago.Carmona@unige.ch
  orcid: https://orcid.org/0000-0002-2495-0671
repository: https://carmonalab.r-universe.dev
repository-code: https://github.com/carmonalab/scECODA
commit: 3a73b11d4b5ab64a1ab1e5e215482904e0b69fff
url: https://github.com/carmonalab/scECODA
date-released: '2026-05-13'
contact:
- family-names: Halter
  given-names: Christian
  email: scecoda.dev@gmail.com
  orcid: https://orcid.org/0009-0009-5479-2246