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scry

This is the development version of scry; for the stable release version, see scry.

Small-Count Analysis Methods for High-Dimensional Data

Bioconductor version: Development (3.18)

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, enter citation("scry")):

Installation

To install this package, start R (version "4.3") and enter: 

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("scry")

For older versions of R, please refer to the appropriate Bioconductor release.

Documentation

To view documentation for the version of this package installed in your system, start R and enter:

browseVignettes("scry")
Overview of Scry Methods HTML R Script
Scry Methods For Larger Datasets HTML R Script
Reference Manual PDF

Details

biocViews DimensionReduction, GeneExpression, Normalization, PrincipalComponent, RNASeq, Sequencing, SingleCell, Software, Transcriptomics
Version 1.13.0
In Bioconductor since BioC 3.11 (R-4.0) (3.5 years)
License Artistic-2.0
Depends R (>= 4.0), stats, methods
Imports DelayedArray, glmpca (>= 0.2.0), Matrix, SingleCellExperiment, SummarizedExperiment, BiocSingular
Linking To
Suggests BiocGenerics, covr, DuoClustering2018, ggplot2, HDF5Array, knitr, markdown, rmarkdown, TENxPBMCData, testthat
System Requirements
Enhances
URL https://bioconductor.org/packages/scry.html
Bug Reports https://github.com/kstreet13/scry/issues
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Package Archives

Follow Installation instructions to use this package in your R session.

Source Package scry_1.13.0.tar.gz
Windows Binary scry_1.13.0.zip
macOS Binary (x86_64) scry_1.13.0.tgz
macOS Binary (arm64)
Source Repository git clone https://git.bioconductor.org/packages/scry
Source Repository (Developer Access) git clone git@git.bioconductor.org:packages/scry
Bioc Package Browser https://code.bioconductor.org/browse/scry/
Package Short Url https://bioconductor.org/packages/scry/
Package Downloads Report Download Stats