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This is the development version of APL; for the stable release version, see APL.

Association Plots

Bioconductor version: Development (3.20)

APL is a package developed for computation of Association Plots (AP), a method for visualization and analysis of single cell transcriptomics data. The main focus of APL is the identification of genes characteristic for individual clusters of cells from input data. The package performs correspondence analysis (CA) and allows to identify cluster-specific genes using Association Plots. Additionally, APL computes the cluster-specificity scores for all genes which allows to rank the genes by their specificity for a selected cell cluster of interest.

Author: Clemens Kohl [cre, aut], Elzbieta Gralinska [aut], Martin Vingron [aut]

Maintainer: Clemens Kohl <kohl.clemens at>

Citation (from within R, enter citation("APL")):


To install this package, start R (version "4.4") and enter:

if (!require("BiocManager", quietly = TRUE))

# The following initializes usage of Bioc devel


For older versions of R, please refer to the appropriate Bioconductor release.


To view documentation for the version of this package installed in your system, start R and enter:

Analyzing data with APL HTML R Script
Reference Manual PDF


biocViews DimensionReduction, GeneExpression, RNASeq, Sequencing, SingleCell, Software, StatisticalMethod
Version 1.9.1
In Bioconductor since BioC 3.15 (R-4.2) (2 years)
License GPL (>= 3)
Depends R (>= 4.2)
Imports reticulate, Matrix, irlba, ggrepel, ggplot2, viridisLite, plotly, Seurat, SingleCellExperiment, magrittr, SummarizedExperiment, topGO, methods, stats, utils,,, rlang
System Requirements python, pytorch, numpy
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Suggests BiocStyle, knitr, rmarkdown, scRNAseq, scater, scran, testthat
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Follow Installation instructions to use this package in your R session.

Source Package APL_1.9.1.tar.gz
Windows Binary
macOS Binary (x86_64) APL_1.9.1.tgz
macOS Binary (arm64) APL_1.9.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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