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Statistical methods for analysing single cell RNA-seq data

Bioconductor version: Release (3.19)

The speckle package contains functions for the analysis of single cell RNA-seq data. The speckle package currently contains functions to analyse differences in cell type proportions. There are also functions to estimate the parameters of the Beta distribution based on a given counts matrix, and a function to normalise a counts matrix to the median library size. There are plotting functions to visualise cell type proportions and the mean-variance relationship in cell type proportions and counts. As our research into specialised analyses of single cell data continues we anticipate that the package will be updated with new functions.

Author: Belinda Phipson [aut, cre]

Maintainer: Belinda Phipson <phipson.b at>

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


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

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


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:

speckle: statistical methods for analysing single cell RNA-seq data HTML R Script
Reference Manual PDF


biocViews GeneExpression, RNASeq, Regression, SingleCell, Software
Version 1.4.0
In Bioconductor since BioC 3.17 (R-4.3) (1 year)
License GPL-3
Depends R (>= 4.2.0)
Imports limma, edgeR, SingleCellExperiment, Seurat, ggplot2, methods, stats, grDevices, graphics
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Suggests BiocStyle, knitr, rmarkdown, statmod, CellBench, scater, patchwork, jsonlite, vdiffr, testthat (>= 3.0.0)
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Follow Installation instructions to use this package in your R session.

Source Package speckle_1.4.0.tar.gz
Windows Binary
macOS Binary (x86_64) speckle_1.4.0.tgz
macOS Binary (arm64) speckle_1.4.0.tgz
Source Repository git clone
Source Repository (Developer Access) git clone
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