Statistical methods for the analysis of flow cytometry data


[Package List] [Top]

Documentation for package ‘flowStats’ version 1.4.0

User Guides and Package Vignettes

Read overview or browse directory.

Help Pages

flowStats-package Statistical methods for flow cytometry data analysis
%in%,flowFrame,lymphFilter-method Automated gating of elliptical cell populations in 2D.
autoGate Automated gating of single populations in 2D
binByRef Bin a test data set using bins previously created by probability binning a control dataset
calcPBChiSquare Probability binning metirc for comparing the probability binned datasets
calcPearsonChi Pearsons chi-square statistic for comparing the probability binned datasets
curvPeaks Parse curv1Filter output
density1d Find most likely separation between positive and negative populations in 1D
flowStats Statistical methods for flow cytometry data analysis
gaussNorm Per-channel normalization based on landmark registration
gpaSet Multi-dimensional normalization of flow cytometry data
iProcrustes Procrustes analysis. Using singular value decomposition (SVD) to determine a linear transformation to align the points in X to the points in a reference matrix Y.
ITN Sample flow cytometry data
landmarkMatrix Compute and cluster high density regions in 1D
lymphFilter Automated gating of elliptical cell populations in 2D.
lymphFilter-class Automated gating of elliptical cell populations in 2D.
lymphGate Automated gating of elliptical cell populations in 2D.
normQA Normalization quality assessment
oneDGate Find most likely separation between positive and negative populations in 1D
plotBins Plots the probability bins overlaid with flowFrame data
proBin Probability binning - a metric for evaluating multivariate differences
quadrantGate Automated quad gating
rangeGate Find most likely separation between positive and negative populations in 1D
warpSet Normalization based on landmark registration