plot,flowClust-method {flowClust} | R Documentation |
This method generates scatterplot revealing the cluster assignment, cluster boundaries according to the specified percentile as well as supplemental information like outliers or filtered observations.
## S4 method for signature 'flowClust': plot(x, data, subset=c(1,2), ellipse=TRUE, show.outlier=TRUE, show.rm=FALSE, include=1:(x@K), main=NULL, grayscale=FALSE, col=(if (grayscale) gray(1/4) else 2:(length(include)+1)), pch=".", cex=0.6, col.outlier=gray(3/4), pch.outlier=".", col.rm=1, pch.rm=1, cex.rm=0.6, ecol=1, elty=1, level=0.9, cutoff=FALSE, npoints=501, add=FALSE, ...)
x |
Object returned from flowClust . |
data |
A matrix, data frame of observations, or object of class flowFrame . This is the object on which flowClust was performed. |
subset |
A numeric vector of length two indicating which two variables are selected for the scatterplot. Alternatively, a character vector containing the names of the two variables is allowed if x@varNames is not NULL . |
ellipse |
A logical value indicating whether the cluster boundary is to be drawn or not. If TRUE , the boundary will be drawn according to the level specified by level or cutoff . |
show.outlier |
A logical value indicating whether outliers will be explicitly shown or not. |
show.rm |
A logical value indicating whether filtered observations will be shown or not. |
include |
A numeric vector specifying which clusters will be shown on the plot. By default, all clusters are included. |
main |
Title of the plot. |
grayscale |
A logical value specifying if a grayscale plot is desired. This argument takes effect only if the default values of relevant graphical arguments are taken. |
col |
Color(s) of the plotting characters. May specify a different color for each cluster. |
pch |
Plotting character(s) of the plotting characters. May specify a different character for each cluster. |
cex |
Size of the plotting characters. May specify a different size for each cluster. |
col.outlier |
Color of the plotting characters denoting outliers. |
pch.outlier |
Plotting character(s) used to denote outliers. May specify a different character for each cluster. |
col.rm |
Color of the plotting characters denoting filtered observations. |
pch.rm |
Plotting character used to denote filtered observations. |
cex.rm |
Size of the plotting character used to denote filtered observations. |
ecol |
Color(s) of the lines representing the cluster boundaries. May specify a different color for each cluster. |
elty |
Line type(s) drawing the cluster boundaries. May specify a different line type for each cluster. |
level |
A numeric value between 0 and 1 specifying the threshold used to call a point an outlier. The default is 0.9, meaning that any point outside the 90% quantile region, shown as the cluster boundary on the graph, will be called an outlier. Note that this argument takes effect only if cutoff is FALSE ; see below for more details. |
cutoff |
Either a logical or numeric value specifying the criterion used to identify outliers and determine cluster boundaries. If TRUE , the criterion stated in x@ruleOutliers will be used; if FALSE (the default), the criterion will be set according to level . Otherwise, a numeric value will be taken as the threshold (e.g., 0.5) for u, a quantity used to measure the degree of “outlyingness” based on the Mahalanobis distance. Please refer to Lo et al. (2008) for more details. |
npoints |
The number of points used to draw each cluster boundary. |
add |
A logical value. If TRUE , add to the current plot. |
... |
Further graphical parameters passed to the generic function plot . |
The cluster boundaries need not be elliptical since Box-Cox transformation has been performed.
Raphael Gottardo <raph@stat.ubc.ca>, Kenneth Lo <c.lo@stat.ubc.ca>
Lo, K., Brinkman, R. R. and Gottardo, R. (2008) Automated Gating of Flow Cytometry Data via Robust Model-based Clustering. Cytometry A 73, 321-332.
res <- flowClust(iris[,1:4], K=3) plot(res, data=iris, subset=c("Sepal.Width", "Petal.Width"), pch=1, pch.outlier=2) plot(res, data=iris, subset=c(2,4), ellipse=FALSE, show.outlier=FALSE, pch=1) plot(res, data=iris, subset=c("Petal.Length", "Petal.Width"), include=c(2,3), pch=1, pch.outlier=1) plot(res, data=iris, subset=c("Petal.Length", "Petal.Width"), include=c(2,3), grayscale=TRUE, pch=1, pch.outlier=1, level=0.8)