simpleSeg

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

A package to perform simple cell segmentation

Bioconductor version: Development (3.18)

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.

Author: Nicolas Canete [aut], Alexander Nicholls [aut], Ellis Patrick [aut, cre]

Maintainer: Ellis Patrick <ellis.patrick at sydney.edu.au>

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

Installation

To install this package, start R (version "4.3") and enter:

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

# The following initializes usage of Bioc devel
BiocManager::install(version='devel')

BiocManager::install("simpleSeg")

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

Documentation

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

browseVignettes("simpleSeg")

Introduction to simpleSeg	HTML	R Script
Reference Manual	PDF
NEWS	Text

Details

biocViews	Classification, Normalization, SingleCell, Software, Survival
Version	1.3.0
In Bioconductor since	BioC 3.16 (R-4.2) (1 year)
License	GPL-3
Depends	R (>= 3.5.0)
Imports	BiocParallel, EBImage, terra, stats, spatstat.geom, S4Vectors, grDevices, SummarizedExperiment, methods, cytomapper
Linking To
Suggests	BiocStyle, testthat (>= 3.0.0), knitr, ggplot2
System Requirements
Enhances
URL	https://github.com/SydneyBioX/simpleSeg
Bug Reports	https://github.com/SydneyBioX/simpleSeg/issues

Depends On Me
Imports Me
Suggests Me	spicyWorkflow
Links To Me
Build Report

Package Archives

Follow Installation instructions to use this package in your R session.

Source Package	simpleSeg_1.3.0.tar.gz
Windows Binary	simpleSeg_1.3.0.zip (64-bit only)
macOS Binary (x86_64)	simpleSeg_1.3.0.tgz
macOS Binary (arm64)	simpleSeg_1.3.0.tgz
Source Repository	git clone https://git.bioconductor.org/packages/simpleSeg
Source Repository (Developer Access)	git clone git@git.bioconductor.org:packages/simpleSeg
Bioc Package Browser	https://code.bioconductor.org/browse/simpleSeg/
Package Short Url	https://bioconductor.org/packages/simpleSeg/
Package Downloads Report	Download Stats