Algorithms and Data Structures for Large Single-Cell Expression Matrices
Overview
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.
Install
Health
- OK13 OK2026-09-25
- ERROR12 OK, 1 ERROR2026-09-18
- OK13 OK2026-08-26
- ERROR12 OK, 1 ERROR2026-08-22
- OK13 OK2026-08-20
Show 16 earlier changesHide 16 earlier changes
- ERROR12 OK, 1 ERROR2026-08-12
- OK13 OK2026-08-08
- ERROR12 OK, 1 ERROR2026-08-07
- OK13 OK2026-08-05
- NOTE12 OK, 1 NOTE2026-08-03
- ERROR12 OK, 1 ERROR2026-08-02
- NOTE12 OK, 1 NOTE2026-08-01
- OK13 OK2026-07-30
- NOTE12 OK, 1 NOTE2026-07-29
- OK13 OK2026-07-26
- ERROR12 OK, 1 ERROR2026-07-19
- OK13 OK2026-07-08
- ERROR12 OK, 1 ERROR2026-07-05
- OK13 OK2026-06-25
- ERROR11 OK, 1 ERROR2026-06-24
- OK7 OK2026-06-18
Documentation
- Help pages
- 8includes a package overview page
- Examples that run
- 100%8 run in a plain check
- Exported functions with examples
- 100%
- Documented parameters
- 100%
- Return-value docs
- 100%
- Help pages citing references
- 0%
Downloads
Repository
- PRs merged (all time)
- 83%
- Median days to close, 50 most recently updated closed issues
- 16
- Median days to close, 50 most recently updated closed PRs
- 0
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5 development-tooling and community-health practices detected across 3 families in the upstream repository
Checks run against github.com/timothy-barry/ondisc on 2026-10-21.
An outside contributor's pull request to this repository was written with an AI coding tool.
- Claude CodePull requests: 1 from outside contributors, first on 2025-06-20, 1 from forks
Dependencies
Installing ondisc adds 28 packages (16 with compiled code, 15 MB of source tarballs). Heaviest: data.table 5.7 MB, Rcpp 1.8 MB, vctrs 1.0 MB. 1 more not on CRAN is not measured.
Code & Tests
Datasets
People & History
Pick two releases to compare their code metrics.
- unarchivedReturned to CRAN2026-06-17
- 1.3.5Latest2026-06-17 · current release · diff ↗ ·
removed 9 exports
create_ondisc_matrix_from_mtx, get_cell_barcodes, get_feature_ids, get_feature_names, metadata_ondisc_matrix, multimodal_ondisc_matrix, ncol, nrow, ondisc_matrixadded 4 exports
create_odm_from_cellranger, create_odm_from_r_matrix, initialize_odm_from_backing_file, write_example_cellranger_dataset - RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- archivedRemoved from CRAN2025-02-02issues were not corrected in time
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- RR 4.2.0 released · 2022-04-22
- RR 4.1.0 released · 2021-05-18
- 1.0.02021-03-05
- RR 4.0.0 released · 2020-04-24
Package metadata
- First published
- 2021-03-05
- Total releases
- 2 / 5 yrs
- License
- MIT + file LICENSE OSI
- Minimum R
- ≥ 4.1.0
- Download size
- 251 KB
Cite
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