Package: Coralysis
Type: Package
Title: Coralysis sensitive identification of imbalanced cell types and
        states in single-cell data via multi-level integration
Version: 1.2.0
Description: Coralysis is an R package featuring a multi-level
        integration algorithm for sensitive integration,
        reference-mapping, and cell-state identification in single-cell
        data. The multi-level integration algorithm is inspired by the
        process of assembling a puzzle - where one begins by grouping
        pieces based on low-to high-level features, such as color and
        shading, before looking into shape and patterns. This approach
        progressively blends the batch effects and separates cell types
        across multiple rounds of divisive clustering.
Authors@R: c(person("António", "Sousa",
             email = "aggode@utu.fi",
             role=c("cre", "aut"), 
             comment = c(ORCID = "0000-0003-4779-6459")),
             person("Johannes", "Smolander",
             role=c("ctb", "aut"), 
             comment = c(ORCID = "0000-0003-3872-9668")),
             person("Sini", "Junttila",
             role=c("aut"), 
             comment = c(ORCID = "0000-0003-3754-5584")),
             person("Laura L", "Elo",
             role=c("aut"), 
             comment = c(ORCID = "0000-0001-5648-4532")))
License: GPL-3
Imports: Matrix, aricode, LiblineaR, SparseM, ggplot2, umap, Rtsne,
        pheatmap, reshape2, dplyr, SingleCellExperiment,
        SummarizedExperiment, S4Vectors, methods, stats, utils, RANN,
        sparseMatrixStats, irlba, flexclust, scran, class, matrixStats,
        tidyr, cowplot, uwot, scatterpie, RColorBrewer, ggrastr,
        ggrepel, RSpectra, BiocParallel, withr
Depends: R (>= 4.2.0)
Suggests: knitr, rmarkdown, bluster, ComplexHeatmap, circlize, scater,
        viridis, scRNAseq, SingleR, MouseGastrulationData, testthat (>=
        3.0.0), BiocStyle, scrapper
Encoding: UTF-8
RoxygenNote: 7.3.2
VignetteBuilder: knitr
biocViews: SingleCell, RNASeq, Proteomics, Transcriptomics,
        GeneExpression, BatchEffect, Clustering, Annotation,
        Classification, DifferentialExpression, DimensionReduction,
        Software
NeedsCompilation: no
URL: https://github.com/elolab/Coralysis,
        https://elolab.github.io/Coralysis/
BugReports: https://github.com/elolab/Coralysis/issues
Config/testthat/edition: 3
Config/pak/sysreqs: libcairo2-dev cmake libfontconfig1-dev
        libfreetype6-dev libfribidi-dev libglpk-dev make
        libharfbuzz-dev libicu-dev libjpeg-dev libpng-dev libtiff-dev
        libuv1-dev libwebp-dev libxml2-dev libssl-dev python3
        zlib1g-dev
Repository: Bioconductor 3.23
Date/Publication: 2026-04-28 13:05:04 UTC
RemoteUrl: https://github.com/bioc/Coralysis
RemoteRef: RELEASE_3_23
RemoteSha: 24c1814b73cad37b5e240754cc5c650e743e69fd
Packaged: 2026-09-17 07:32:53 UTC; root
Author: António Sousa [cre, aut] (ORCID:
    <https://orcid.org/0000-0003-4779-6459>),
  Johannes Smolander [ctb, aut] (ORCID:
    <https://orcid.org/0000-0003-3872-9668>),
  Sini Junttila [aut] (ORCID: <https://orcid.org/0000-0003-3754-5584>),
  Laura L Elo [aut] (ORCID: <https://orcid.org/0000-0001-5648-4532>)
Maintainer: António Sousa <aggode@utu.fi>