Package: CelliD
Type: Package
Title: Unbiased Extraction of Single Cell gene signatures using
        Multiple Correspondence Analysis
Version: 1.6.2
Authors@R: c(person("Akira", "Cortal", email = "akira.cortal@institutimagine.org",
  role = c("aut", "cre")),  person("Antonio", "Rausell", role= c("aut", "ctb"), email = "antonio.rausell@institutimagine.org"))
Description: CelliD is a clustering-free multivariate statistical method for the robust extraction of per-cell gene signatures from single-cell RNA-seq. 
  CelliD allows unbiased cell identity recognition across different donors, tissues-of-origin, model organisms and single-cell omics protocols. 
  The package can also be used to explore functional pathways enrichment in single cell data. 
Depends: R (>= 4.1), Seurat (>= 4.0.1), SingleCellExperiment
License: GPL-3 + file LICENSE
Encoding: UTF-8
LazyData: true
Imports: Rcpp, RcppArmadillo, stats, utils, Matrix, tictoc, scater,
        stringr, irlba, data.table, glue, pbapply, umap, Rtsne,
        reticulate, fastmatch, matrixStats, ggplot2, BiocParallel,
        SummarizedExperiment, fgsea
Suggests: knitr, rmarkdown, BiocStyle, testthat, tidyverse, ggpubr,
        destiny, ggrepel
VignetteBuilder: knitr
RoxygenNote: 7.1.1
biocViews: RNASeq, SingleCell, DimensionReduction, Clustering,
        GeneSetEnrichment, GeneExpression, ATACSeq
LinkingTo: Rcpp, RcppArmadillo
git_url: https://git.bioconductor.org/packages/CelliD
git_branch: RELEASE_3_16
git_last_commit: 92f1ce7
git_last_commit_date: 2023-01-19
Date/Publication: 2023-01-19
NeedsCompilation: yes
Packaged: 2023-01-19 22:46:43 UTC; biocbuild
Author: Akira Cortal [aut, cre],
  Antonio Rausell [aut, ctb]
Maintainer: Akira Cortal <akira.cortal@institutimagine.org>
Built: R 4.2.2; x86_64-w64-mingw32; 2023-01-20 12:29:45 UTC; windows
ExperimentalWindowsRuntime: ucrt
Archs: x64
