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 in 1D |
autoGate |
Automated gating of single populations in 2D |
BackGating |
Sample backgating results |
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 |
idFeatures |
(Internal use only) Identify features of flow cytometry data using backgating |
idFeaturesByBackgating |
(Internal use only) Identify features of flow cytometry data using backgating |
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 |
rangeFilter |
Find most likely separation between positive and negative populations in 1D |
rangeFilter-class |
Find most likely separation between positive and negative populations in 1D |
rangeGate |
Find most likely separation between positive and negative populations in 1D |
warpSet |
Normalization based on landmark registration |