Statistical methods for the analysis of flow cytometry data


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Documentation for package ‘flowStats’ version 1.8.0

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flowStats-package Statistical methods for flow cytometry data analysis
%in%-method Automated gating of elliptical cell populations in 2D.
%in%-method Find most likely separation between positive and negative populations
autoGate Automated gating of single populations in 2D
BackGating Sample backgating results
binByRef Bin a test data set using bins previously created by probability
calcPBChiSquare Probability binning metirc for comparing the probability binned
calcPearsonChi Pearsons chi-square statistic for comparing the probability binned
curvPeaks Parse curv1Filter output
density1d Find most likely separation between positive and negative populations
flowStats Statistical methods for flow cytometry data analysis
gaussNorm Per-channel normalization based on landmark registration
gpaSet Multi-dimensional normalization of flow cytometry data
idFeatures (Internal use only) Identify features of flow cytometry data using
idFeaturesByBackgating (Internal use only) Identify features of flow cytometry data using
iProcrustes Procrustes analysis. Using singular value decomposition (SVD) to
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
plotBins Plots the probability bins overlaid with flowFrame data
proBin Probability binning - a metric for evaluating multivariate differences
quadrantGate Automated quad gating
rangeFilter Find most likely separation between positive and negative populations
rangeFilter-class Find most likely separation between positive and negative populations
rangeGate Find most likely separation between positive and negative populations
warpSet Normalization based on landmark registration