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simpleSeg

A package to perform simple cell segmentation

Bioconductor version: 3.23 · Package version: 1.14.0

Image segmentation is the process of identifying the borders of individual objects (in this case cells) within an image. This allows for the features of cells such as marker expression and morphology to be extracted, stored and analysed. simpleSeg provides functionality for user friendly, watershed based segmentation on multiplexed cellular images in R based on the intensity of user specified protein marker channels. simpleSeg can also be used for the normalization of single cell data obtained from multiple images.

Installation

if (!require("BiocManager", quietly = TRUE))
    install.packages("BiocManager")

BiocManager::install("simpleSeg")

Details

MaintainerEllis Patrick <ellis.patrick@sydney.edu.au>
AuthorNicolas Canete [aut], Alexander Nicholls [aut], Ellis Patrick [aut, cre]
LicenseGPL-3
URLhttps://sydneybiox.github.io/simpleSeg/ https://github.com/SydneyBioX/simpleSeg
Bug Reportshttps://github.com/SydneyBioX/simpleSeg/issues
Downloads rank543
Source branchRELEASE_3_23
biocViewsClassification, Normalization, SingleCell, Software, Spatial, Survival

Documentation

Download

Follow the installation instructions to use this package in your R session.

Source packagesimpleSeg_1.14.0.tar.gz
Windows binary (x86_64)simpleSeg_1.14.0.zip
macOS binary (arm64)simpleSeg_1.14.0.tgz
macOS binary (x86_64)simpleSeg_1.14.0.tgz
Dependencies

Depends: R (>= 3.5.0)

Imports: BiocParallel, EBImage, terra, stats, spatstat.geom, S4Vectors, grDevices, SummarizedExperiment, methods, cytomapper

Suggests: BiocStyle, testthat (>= 3.0.0), knitr, ggplot2

Reverse dependencies

Imports Me (2): lisaClust, spicyR