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DESCRIPTION
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Package: ondisc
Title: Algorithms and data structures for large single-cell expression matrices
Version: 1.2.0
Authors@R:
c(person(given = "Timothy",
family = "Barry",
role = c("aut", "cre"),
email = "[email protected]",
comment=c(ORCID="0000-0002-4356-627X")),
person(given = "Songcheng",
family = "Dai",
role = "ctb"),
person(given = "Yixuan",
family = "Qiu",
role = "ctb"),
person(given = "Eugene",
family = "Katsevich",
role = c("aut", "ths"),
email = "[email protected]"))
Description: 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.
License: MIT + file LICENSE
Encoding: UTF-8
Roxygen: list(markdown = TRUE)
LinkingTo: Rcpp, Rhdf5lib
biocViews: DataImport, SingleCell, DifferentialExpression, CRISPR
RoxygenNote: 7.3.1
Imports:
crayon,
data.table,
methods,
Rcpp,
Rhdf5lib,
dplyr,
readr
SystemRequirements: GNU make
Suggests:
sessioninfo,
knitr,
Matrix,
R.utils,
rmarkdown,
sceptredata,
testthat (>= 3.0.0)
Remotes: github::katsevich-lab/sceptre, github::katsevich-lab/sceptredata
Config/testthat/edition: 3
URL: https://timothy-barry.github.io/ondisc/, https://timothy-barry.github.io/sceptre-book/
BugReports: https://github.com/timothy-barry/ondisc/issues
VignetteBuilder: knitr