scry

Small-Count Analysis Methods for High-Dimensional Data

Bioconductor version: 3.23 · Package version: 1.24.0

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.

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

BiocManager::install("scry")