This is the released version of CelliD; for the devel version, see CelliD.
Unbiased Extraction of Single Cell gene signatures using Multiple Correspondence AnalysisBioconductor version: Release (3.21)
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.
Author: Akira Cortal [aut, cre], Antonio Rausell [aut, ctb]
Maintainer: Akira Cortal <akira.cortal at institutimagine.org>
Citation (from within R, entercitation("CelliD")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("CelliD")
For older versions of R, please refer to the appropriate Bioconductor release.
DocumentationTo view documentation for the version of this package installed in your system, start R and enter:
browseVignettes("CelliD")
Details biocViews ATACSeq, Clustering, DimensionReduction, GeneExpression, GeneSetEnrichment, RNASeq, SingleCell, Software Version 1.16.0 In Bioconductor since BioC 3.13 (R-4.1) (4 years) License GPL-3 + file LICENSE Depends R (>= 4.1), Seurat (>= 4.0.1), SingleCellExperiment Imports Rcpp, RcppArmadillo, stats, utils, Matrix, tictoc, scater, stringr, irlba, data.table, glue, pbapply, umap, Rtsne, reticulate, fastmatch, matrixStats, ggplot2, BiocParallel, SummarizedExperiment, fgsea System Requirements URL See More Package Archives
Follow Installation instructions to use this package in your R session.
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