scry
Small-Count Analysis Methods for High-Dimensional Data
Bioconductor version: Release (3.19)
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 | 1.16.0 |
| 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_1.16.0.tar.gz |
| Windows Binary (x86_64) | scry_1.16.0.zip |
| macOS Binary (x86_64) | scry_1.16.0.tgz |
| macOS Binary (arm64) | scry_1.16.0.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 |