kstreet13/scry: Small-Count Analysis Methods for High-Dimensional Data

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.

Getting started

Package details

Bioconductor views DimensionReduction GeneExpression Normalization PrincipalComponent RNASeq Sequencing SingleCell Software Transcriptomics
Maintainer
LicenseArtistic-2.0
Version1.1.1
URL https://bioconductor.org/packages/scry.html
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("kstreet13/scry")
kstreet13/scry documentation built on Oct. 15, 2020, 7:20 p.m.