Package: presto 1.1.0

presto: Fast Functions for Differential Expression Using Wilcoxon and AUC

Scalable implementation of the Wilcoxon rank sum test and the area under the receiver operating characteristic curve (also known as auROC or AUC) statistic. Interfaces to dense and sparse matrices, as well as the genomics analysis frameworks 'Seurat' and 'SingleCellExperiment'.

Authors:Ilya Korsunsky [aut], Aparna Nathan [aut], Nghia Millard [aut], Soumya Raychaudhuri [aut], Kamil Slowikowski [cre, ctb], Austin Hartman [ctb]

presto_1.1.0.tar.gz
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presto_1.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
presto/json (API)

# Install 'presto' in R:
install.packages('presto', repos = c('https://slowkow.r-universe.dev', 'https://cloud.r-project.org'))
Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

cpp

6.59 score 1 packages 1.5k scripts 8.7k downloads 16 exports 25 dependencies

Last updated from:5e323fb82d. Checks:15 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK190
linux-devel-x86_64OK244
source / vignettesOK231
linux-release-arm64OK176
linux-release-x86_64OK203
macos-release-arm64OK191
macos-release-x86_64OK320
macos-oldrel-arm64OK115
macos-oldrel-x86_64OK546
windows-devel-arm64OK423
windows-devel-x86_64OK185
windows-release-arm64OK389
windows-release-x86_64OK184
windows-oldrel-x86_64OK183
wasm-releaseOK143

Exports:%>%collapse_countscompute_hashnnzeroGroupspseudobulk_deseq2pseudobulk_one_vs_allpseudobulk_pairwisepseudobulk_withinrank_matrixsumGroupssummarize_dge_pairstop_markerstop_markers_ddstoy_scetoy_seuratwilcoxauc

Dependencies:clicpp11data.tabledplyrgenericsgluelatticelifecyclemagrittrMatrixpillarpkgconfigpurrrR6RcppRcppArmadillorlangstringistringrtibbletidyrtidyselectutf8vctrswithr

Getting started with presto
Demo data | Quick start | Result columns | Top markers per cluster | Restricting to a subset of groups | Seurat and SingleCellExperiment | Notes on input types | Session info
Rendered fromgetting-started.Rmdusingknitr::rmarkdown

Last update: 2026-09-30
Started: 2026-09-30

Pseudobulk differential expression with DESeq2
Why pseudobulk? | Demo data | Step 1: collapse cells to pseudobulks | Step 2: one-vs-all DESeq2 | Step 3: top markers per cluster | Step 4: pairwise cluster contrasts | Step 5: within-cluster Case vs Control | Tips | Session info
Rendered frompseudobulk.Rmdusingknitr::rmarkdown

Last update: 2026-09-30
Started: 2026-09-30