calcPBChiSquare: Probability binning metirc for comparing the probability...

In RGLab/flowStats: Statistical methods for the analysis of flow cytometry data

Probability binning metirc for comparing the probability binned datasets

Description

This function calculates the Probability binning metric proposed by Baggerly et al. The function utilizes the data binned using the proBin and binByRef functions.

Usage

calcPBChiSquare(ctrlRes,sampRes,ctrlCount,sampCount)

Arguments

ctrlRes	The result generated by calling the probBin function on a control dataset.
sampRes	The result generated by calling the byByRef function on a test sample dataset
ctrlCount	The number of events in the control sample
sampCount	The number of events in the test sample being compared

Value

A list containing the statistic, p.value, observed, expected counts and the residuals

Author(s)

Nishant Gopalakrishnan

See Also

proBin, calcPBChiSquare

Examples

library(flowCore)
data(GvHD)
# flow frame 1 is treated as  control dataset and used to generate bins
resCtrl<-proBin(GvHD[[1]][,c("FSC-H","SSC-H","Time")],200)  
plotBins(resCtrl,GvHD[[1]],channels=c("FSC-H","SSC-H","Time"),title="Binned control data")
# Same bins are applied to flowFrame 16
resSample<-binByRef(resCtrl,GvHD[[16]][,c("FSC-H","SSC-H","Time")])
ctrlCount<-nrow(GvHD[[1]])
sampCount<-nrow(GvHD[[16]])
stat<-calcPBChiSquare(resCtrl,resSample,ctrlCount,sampCount)

RGLab/flowStats documentation built on July 20, 2023, 1:33 a.m.