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 of
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 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.
| Version: |
1.3.5 |
| Depends: |
R (≥ 4.1.0) |
| Imports: |
crayon, data.table, methods, Rcpp, Rhdf5lib, dplyr, readr, Matrix |
| LinkingTo: |
Rcpp, Rhdf5lib |
| Suggests: |
sessioninfo, knitr, R.utils, rmarkdown, testthat (≥ 3.0.0) |
| Published: |
2026-06-17 |
| DOI: |
10.32614/CRAN.package.ondisc |
| Author: |
Timothy Barry 
[aut, cre],
Songcheng Dai [ctb],
Yixuan Qiu [ctb],
Eugene Katsevich [aut, ths] |
| Maintainer: |
Timothy Barry <tbarry at hsph.harvard.edu> |
| BugReports: |
https://github.com/timothy-barry/ondisc/issues |
| License: |
MIT + file LICENSE |
| URL: |
https://timothy-barry.github.io/ondisc/,
https://timothy-barry.github.io/sceptre-book/ |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Materials: |
README, NEWS |
| CRAN checks: |
ondisc results |
Documentation:
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