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Rcell
=====

Microscopy Based Cytometry Data Analysis Package for R

A package to analyze microscopy based cytometry datasets. It was originally design for Cell-ID, but can be adapted to other image segmentation programs. It includes functions for loading, manipulating and plotting the data. It can also create automatic image montages of cells in a user defined layout.

To install from CRAN:

	* Install Rcell
	R> install.packages("Rcell")

	* Install suggested packages 
	R> install.packages(c("Hmisc","RcellData")) 
	R> source("http://bioconductor.org/biocLite.R") 
	R> biocLite("EBImage")

To install from source:

	*  download RcellExtra_{version}.tar.gz

	*  Install dependendecies
	R> install.packages(c("proto","plyr","reshape","ggplot2","digest")) #required
	R> install.packages(c("Hmisc","RcellData")) #suggested
	R> source("http://bioconductor.org/biocLite.R")
	R> biocLite("EBImage")
	
	*  Install Rcell
	R> install.packages( _path_to_Rcell_, repos = NULL, type="source")

_path_to_Rcell_ should be somethig like "C:\Users\User\Downloads\Rcell_1.3-1.tar.gz" in windows or "~/Downloads/Rcell_1.3-1.tar.gz" in Mac/Linux.

To get started read the vignette:

	R> vignette("Rcell")

To use the extra functions provided in RcellExtra:

	*  download RcellExtra_{version}.tar.gz

	*  Install dependendecies		
	R> install.packages( c("chron", "R.matlab", "splancs"))
	R> source("http://bioconductor.org/biocLite.R")
	R> biocLite("hopach")
	
	*  Install RcellExtra
	R> install.packages( _path_to_RcellExtra_ , repos = NULL, type="source")

_path_to_RcellExtra_ should be somethig like "C:\Users\User\Downloads\RcellExtra_1.3-1.tar.gz" in windows or "~/Downloads/RcellExtra_1.3-1.tar.gz" in Mac/Linux.
Source: README.txt, updated 2015-06-08