A data frame containing subpopulations on channels of
interests. Must be a returning result from flowStats:::backGating
nDim
An integer indicating the length of channels of interest.
thres.sigma
An numerical value indicating the threshold at
which to cut tree, e.g., as resulting from 'diana', into several clusters.
lambda
A numerical value indicating the percentage of the
potential features that is used as a threshold for deciding outlier
clusters. The default value is 0.1.
reference.method
A character vector indicating the method for
computing the reference features. If median, the reference
feature is defined by the medain of eac cluster of features. Valid
methods include median and mean only.
plot.workflow
Logical. If TURE, display the workflow of feature
identification.
ask
Logical. If TRUE, the display operates in interactive mode.
Details
Using the resulting data frame from backGating as potential
features, the algorithm follows four major steps: (i) centering
the potential features, which yields the returning value
TransMatrix, (ii) using diana to compute a clustering of
the potential features, (iii) cutting the tree into several clusters,
and (iv) accessing outliers and rendering the final registered
features with labels.
In step three, the threshold for cutting the tree is computed by
sd * thres.sigma,
where sd is the standard deviation of the distribution of the
height between entities computed by diana.
A cluster is determined as an outlier if the number of its members is
less than the median of the numbers of all clusters' members times 'lambda'.
Value
register
A list containing registered features for each sample.
R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
Copyright (C) 2016 The R Foundation for Statistical Computing
Platform: x86_64-pc-linux-gnu (64-bit)
R is free software and comes with ABSOLUTELY NO WARRANTY.
You are welcome to redistribute it under certain conditions.
Type 'license()' or 'licence()' for distribution details.
R is a collaborative project with many contributors.
Type 'contributors()' for more information and
'citation()' on how to cite R or R packages in publications.
Type 'demo()' for some demos, 'help()' for on-line help, or
'help.start()' for an HTML browser interface to help.
Type 'q()' to quit R.
> library(flowStats)
Loading required package: flowCore
Loading required package: fda
Loading required package: splines
Loading required package: Matrix
Attaching package: 'Matrix'
The following object is masked from 'package:flowCore':
%&%
Attaching package: 'fda'
The following object is masked from 'package:graphics':
matplot
Loading required package: mvoutlier
Loading required package: sgeostat
sROC 0.1-2 loaded
Loading required package: cluster
Loading required package: flowWorkspace
Loading required package: flowViz
Loading required package: lattice
Loading required package: ncdfFlow
Loading required package: RcppArmadillo
Loading required package: BH
Loading required package: gridExtra
> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/flowStats/idFeaturesByBackgating.Rd_%03d_medium.png", width=480, height=480)
> ### Name: idFeaturesByBackgating
> ### Title: (Internal use only) Identify features of flow cytometry data
> ### using backgating
> ### Aliases: idFeatures idFeaturesByBackgating
> ### Keywords: misc
>
> ### ** Examples
>
> ## Not run:
> ##D data(ITN)
> ##D wf <- workFlow(ITN)
> ##D tl <- transformList(colnames(ITN)[3:7], asinh, transformationId="asinh")
> ##D dat <- trnasformList(ITN, tl)
> ##D bg <- backGating(dat, xy=c("FSC", "SSC"), channels="CD3")
> ## End(Not run)
>
> data(BackGating)
> results <- flowStats:::idFeaturesByBackgating(bg=BackGating, nDim=2,
+ plot.workflow=TRUE, ask=TRUE)
NULL
NULL
>
>
>
>
>
>
> dev.off()
null device
1
>