GateFinder-package {GateFinder} | R Documentation |
Given a vector of cluster memberships for a cell population, identifies a sequence of gates (polygon filters on 2D scatter plots) for isolation of that cell type.
Package: | GateFinder |
Type: | Package |
Version: | 1.0 |
Date: | 2013-12-21 |
License: | Artistic-2.0 |
~~ An overview of how to use the package, including the most important ~~ ~~ functions ~~
Nima Aghaeepour <naghaeep@gmail.com> and Erin F. Simonds <erin.simonds@gmail.com>
library(flowCore) data(LPSData) ##Select the target population. In this case cells with those with a pP38 expression (dimension 34) of higher than 3.5. targetpop <- (exprs(rawdata)[,34]>3.5) ##Subset the markers that should be considered for gating. x=exprs(rawdata)[,prop.markers] colnames(x)=marker.names[prop.markers] ##Run GateFinder. ans=GateFinder(x, targetpop) ##Make the plots. plot (x, ans, c(2,3), targetpop) plot(ans) ##Alternatively, using a flowFrame: x=new('flowFrame', exprs=x) ans=GateFinder(x, targetpop) ##Now you can use the gates and filters to subset the flowFrame. E.g.: split(x, ans@flowEnv$Filter2) ##This function relies on an EXPERIMENTAL feature in flowUtils. Please be cautious when replying on this. ##Don't run without the optional flowUtils package installed. ##To write the gates into a GatingML file: ##library(flowUtils) ##write.gatingML(ans@flowEnv, 'GatingML.xml')