scry
This is the released version of scry; for the devel version, see scry.
Small-Count Analysis Methods for High-Dimensional Data
Bioconductor version: Release (3.20)
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("scry")
):
Installation
To install this package, start R (version "4.4") 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.
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 |
Details
biocViews | DimensionReduction, GeneExpression, Normalization, PrincipalComponent, RNASeq, Sequencing, SingleCell, Software, Transcriptomics |
Version | 1.18.0 |
In Bioconductor since | BioC 3.11 (R-4.0) (4.5 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
Suggests | BiocGenerics, covr, DuoClustering2018, ggplot2, HDF5Array, knitr, markdown, rmarkdown, TENxPBMCData, testthat |
Linking To | |
Enhances | |
Depends On Me | |
Imports Me | |
Suggests Me | |
Links To Me | |
Build Report | Build Report |
Package Archives
Follow Installation instructions to use this package in your R session.
Source Package | scry_1.18.0.tar.gz |
Windows Binary (x86_64) | scry_1.18.0.zip |
macOS Binary (x86_64) | scry_1.18.0.tgz |
macOS Binary (arm64) | scry_1.18.0.tgz |
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 |