This is the released version of scry; for the devel version, see scry.
Small-Count Analysis Methods for High-Dimensional DataBioconductor version: Release (3.21)
Many modern biological datasets consist of small counts that are not well fit by standard linear-Gaussian methods such as principal component analysis. This package provides implementations of count-based feature selection and dimension reduction algorithms. These methods can be used to facilitate unsupervised analysis of any high-dimensional data such as single-cell RNA-seq.
Author: Kelly Street [aut, cre], F. William Townes [aut, cph], Davide Risso [aut], Stephanie Hicks [aut]
Maintainer: Kelly Street <street.kelly at gmail.com>
Citation (from within R, entercitation("scry")
): Installation
To install this package, start R (version "4.5") and enter:
if (!require("BiocManager", quietly = TRUE))
install.packages("BiocManager")
BiocManager::install("scry")
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("scry")
Details biocViews DimensionReduction, GeneExpression, Normalization, PrincipalComponent, RNASeq, Sequencing, SingleCell, Software, Transcriptomics Version 1.20.0 In Bioconductor since BioC 3.11 (R-4.0) (5 years) License Artistic-2.0 Depends R (>= 4.0), stats, methods Imports DelayedArray, glmpca (>= 0.2.0), Matrix, SingleCellExperiment, SummarizedExperiment, BiocSingular System Requirements URL https://bioconductor.org/packages/scry.html Bug Reports https://github.com/kstreet13/scry/issues See More Package Archives
Follow Installation instructions to use this package in your R session.
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