Package: cellpaintr 0.99.3

Christof Seiler

cellpaintr: Perturbation Analysis for Cell Painting Data

This package load cell painting data into R and preprocess feature to make them ready for machine learning. We use random forest to predict cell perturbations from CellProfiler features. We summarize the results in a volcano plot.

Authors:Christof Seiler [aut, cre], Phatthamon Laphanuwat [ctb], Caroline Ospelt [ctb], European League Against Rheumatism [fnd], Swiss National Science Foundation [fnd]

cellpaintr_0.99.3.tar.gz
cellpaintr_0.99.3.zip(r-4.7-any)cellpaintr_0.99.3.zip(r-4.6-any)cellpaintr_0.99.3.zip(r-4.5-any)
cellpaintr_0.99.3.tgz(r-4.6-any)cellpaintr_0.99.3.tgz(r-4.5-any)
cellpaintr_0.99.3.tar.gz(r-4.7-any)cellpaintr_0.99.3.tar.gz(r-4.6-any)
cellpaintr_0.99.3.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
cellpaintr/json (API)

# Install 'cellpaintr' in R:

install.packages('cellpaintr', repos = c('https://biocstaging.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/christofseiler/cellpaintr/issues

Pkgdown/docs site:https://christofseiler.github.io

On CRAN:

singlecell software classification featureextraction preprocessing visualization

3.85 score 1 stars 2 scripts 16 exports 82 dependencies

Last updated from:7b091cd816. Checks:1 NOTE, 9 OK. Indexed: yes.

Target	Result	Time
bioc-checks	NOTE	203
linux-devel	OK	332
source / vignettes	OK	350
linux-release	OK	327
macos-release	OK	299
macos-oldrel	OK	216
windows-devel	OK	271
windows-release	OK	267
windows-oldrel	OK	235
wasm-release	OK	173

Exports:calculateStats generate_data loadData plotAUC plotCellsPerImage plotLOO plotPCACor plotROC predictLOO removeLowVariance removeNAs removeOutliers removeRowColEffect removeZeroInflation transformScale volcanoPlot

Dependencies:abind assorthead beachmat Biobase BiocGenerics biocmake BiocNeighbors bit bit64 cli clipr codetools cpp11 crayon DelayedArray digest dir.expiry dplyr farver filelock furrr future generics GenomicRanges ggplot2 ggrepel globals glue gtable hardhat hms IRanges isoband labeling lattice lifecycle listenv magrittr Matrix MatrixGenerics matrixStats parallelly parsnip pillar pkgconfig prettyunits progress purrr R6 ranger RColorBrewer Rcpp RcppEigen readr Rigraphlib rlang rsample S4Arrays S4Vectors S7 scales scrapper Seqinfo SingleCellExperiment slider SparseArray sparsevctrs stringi stringr SummarizedExperiment tibble tidyr tidyselect tzdb utf8 vctrs viridisLite vroom warp withr XVector yardstick

cellpaintr Vignette

Rendered fromcellpaintr-vignette.Rmdusingknitr::rmarkdown

Last update: 2026-08-14
Started: 2026-06-25

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Aggregate predicted leave-one-out probabilities over meta variables	aggregateYhat
Aggregate predicted leave-one-out probabilities over meta variables over a list of SingleCellExperiment objects	calculateStats
Internal function to compute y_hat on a subset of the features	compute_y_hat
Simulate CellProfiler data and write to a temporary file	generate_data
Load cell painting data from file and convert to a SingleCellExperiment	loadData
Plot AUC comparison	plotAUC
Plot number of cells per image	plotCellsPerImage
Plot predicted leave-one-out probabilities	plotLOO
Plot number of cells per image	plotPCACor
Plot ROC curves	plotROC
Predict target from features	predictLOO
Filter low variance features	removeLowVariance
Remove cells with missing features	removeNAs
Remove cells if not enough or too many in one image	removeOutliers
Remove row and column effect using the median polish procedure	removeRowColEffect
Remove zero-inflated features	removeZeroInflation
Transform, center, and scale features	transformScale
Plot predicted leave-one-out probabilities	volcanoPlot