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.
Package details |
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| Author | Timothy Barry [aut, cre] (ORCID: <https://orcid.org/0000-0002-4356-627X>), Songcheng Dai [ctb], Yixuan Qiu [ctb], Eugene Katsevich [aut, ths] |
| Bioconductor views | CRISPR DataImport DifferentialExpression SingleCell |
| Maintainer | Timothy Barry <tbarry@hsph.harvard.edu> |
| License | MIT + file LICENSE |
| Version | 1.3.5 |
| URL | https://timothy-barry.github.io/ondisc/ https://timothy-barry.github.io/sceptre-book/ |
| Package repository | View on CRAN |
| Installation |
Install the latest version of this package by entering the following in R:
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