timothy-barry/ondisc: Algorithms and data structures for large single-cell expression matrices

Single-cell datasets are growing in size, posing challenges as well as opportunities for genomics researchers. `ondisc` is an R package that facilitates analysis of large-scale single-cell data out-of-core on a laptop or distributed across tens to hundreds processors on a cluster or cloud. In both of these settings, `ondisc` requires only a few gigabytes of memory, even if the input data are tens of gigabytes in size. `ondisc` mainly is oriented toward single-cell CRISPR screen analysis, but ondisc also can be used for single-cell differential expression and single-cell co-expression analyses. ondisc is powered by several new, efficient algorithms for manipulating and querying large, sparse expression matrices.

Getting started

Package details

Bioconductor views CRISPR DataImport DifferentialExpression SingleCell
Maintainer
LicenseMIT + file LICENSE
Version1.2.0
URL https://timothy-barry.github.io/ondisc/ https://timothy-barry.github.io/sceptre-book/
Package repositoryView on GitHub
Installation Install the latest version of this package by entering the following in R:
install.packages("remotes")
remotes::install_github("timothy-barry/ondisc")
timothy-barry/ondisc documentation built on April 14, 2024, 1:11 a.m.