Package: scECODA
Title: Single-Cell Exploratory Compositional Data Analysis
Version: 1.0.0
Authors@R: c(
    person("Christian", "Halter",
      email = "scecoda.dev@gmail.com",
      role = c("aut", "cre"),
      comment = c(ORCID = '0009-0009-5479-2246')),
    person("Massimo", "Andreatta",
      email = "Massimo.Andreatta@unige.ch",
      role = c("aut"),
      comment = c(ORCID = '0000-0002-8036-2647')),
    person("Santiago", "Carmona",
      email = "Santiago.Carmona@unige.ch",
      role = c("aut"),
      comment = c(ORCID = '0000-0002-2495-0671')),
    person("Swiss Cancer Research Foundation", role = c("fnd"))
    )
Description: 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.
biocViews: Software, SingleCell, Transcriptomics, CellBasedAssays,
        Normalization, Preprocessing, Visualization, Clustering,
        DimensionReduction, FeatureExtraction, PrincipalComponent
BugReports: https://github.com/carmonalab/scECODA/issues
License: GPL-3 + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.3.3
Depends: R (>= 4.5.0)
VignetteBuilder: knitr
Suggests: Seurat (>= 5.0.0), igraph, knitr, rmarkdown, BiocStyle,
        testthat, scRNAseq
Config/testthat/edition: 3
URL: https://github.com/carmonalab/scECODA
Imports: BiocGenerics, cluster, corrplot, DESeq2, dplyr, factoextra (>=
        2.0.0), ggplot2, ggpubr, ggrepel, gtools, Matrix, mclust,
        methods, pheatmap, plotly, rlang, rstatix, S4Vectors, stringr,
        SummarizedExperiment (>= 1.34.0), tidyr, vegan
Config/pak/sysreqs: cmake make libicu-dev libuv1-dev libssl-dev
        zlib1g-dev
Repository: https://bioc-release.r-universe.dev
Date/Publication: 2026-04-28 13:07:02 UTC
RemoteUrl: https://github.com/bioc/scECODA
RemoteRef: RELEASE_3_23
RemoteSha: 7eb703af84625cbe3e23ff536f29c5d589bcbc4e
NeedsCompilation: no
Packaged: 2026-04-30 06:25:34 UTC; root
Author: Christian Halter [aut, cre] (ORCID:
    <https://orcid.org/0009-0009-5479-2246>),
  Massimo Andreatta [aut] (ORCID:
    <https://orcid.org/0000-0002-8036-2647>),
  Santiago Carmona [aut] (ORCID: <https://orcid.org/0000-0002-2495-0671>),
  Swiss Cancer Research Foundation [fnd]
Maintainer: Christian Halter <scecoda.dev@gmail.com>
Built: R 4.6.0; ; 2026-04-30 06:50:06 UTC; windows
