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Single-cell datasets are growing in size, posing challenges as well as opportunities for biology researchers. 'ondisc' (short for "on-disk single cell") enables users to easily and efficiently analyze large-scale single-cell data. 'ondisc' makes computing on large-scale single-cell data FUN: Fast, Universal, and iNtuitive.
Version: | 1.0.0 |
Depends: | R (≥ 3.5.0) |
Imports: | readr, methods, magrittr, rhdf5, data.table, Matrix, Rcpp, crayon, dplyr |
LinkingTo: | Rcpp, Rhdf5lib |
Suggests: | testthat, knitr, rmarkdown, covr |
Published: | 2021-03-05 |
DOI: | 10.32614/CRAN.package.ondisc |
Author: | Timothy Barry |
Maintainer: | Timothy Barry <tbarry2 at andrew.cmu.edu> |
License: | MIT + file LICENSE |
URL: | https://timothy-barry.github.io/ondisc/ |
NeedsCompilation: | yes |
SystemRequirements: | GNU make |
Materials: | README |
CRAN checks: | ondisc results |
Reference manual: | ondisc.pdf |
Vignettes: |
Tutorial 1: Using the 'ondisc_matrix' class Tutorial 2: Using 'metadata_ondisc_matrix' and 'multimodal_ondisc_matrix' |
Package source: | ondisc_1.0.0.tar.gz |
Windows binaries: | r-devel: ondisc_1.0.0.zip, r-release: ondisc_1.0.0.zip, r-oldrel: ondisc_1.0.0.zip |
macOS binaries: | r-release (arm64): ondisc_1.0.0.tgz, r-oldrel (arm64): ondisc_1.0.0.tgz, r-release (x86_64): ondisc_1.0.0.tgz, r-oldrel (x86_64): ondisc_1.0.0.tgz |
Please use the canonical form https://CRAN.R-project.org/package=ondisc to link to this page.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.