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
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:
kstreet13/scry documentation built on Nov. 24, 2022, 7:55 a.m.