computeItemsSampleGUI: GUI to estimate the number of cells in colonies for each...

In RclusTool: Graphical Toolbox for Clustering and Classification of Data Frames

GUI to estimate the number of cells in colonies for each cluster

Description

Open a Graphical User Interface allowing to choose cluster name and model file for the estimation and the saving of the number of cells in colonies.

Usage

computeItemsSampleGUI(
  data.sample,
  method.select = "K-means",
  RclusTool.env = initParameters()
)

Arguments

data.sample	list containing features, profiles and clustering results.
method.select	character vector specifying the name of the clustering result to use ('K-means' by default).
RclusTool.env	environment in which all global parameters, raw data and results are stored.

Details

computeItemsSampleGUI opens a Graphical User Interface allowing to choose cluster name and model file for the estimation and the saving of the number of cells in colonies

Value

data.sample with saved count results

csv file containing the counts.

Examples

 

dat <- rbind(matrix(rnorm(100, mean = 0, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 2, sd = 0.3), ncol = 2), 
             matrix(rnorm(100, mean = 4, sd = 0.3), ncol = 2))
tf <- tempfile()
write.table(dat, tf, sep=",", dec=".")
x <- importSample(file.features=tf)

x <- computeUnSupervised(x, K=0, pca=TRUE, echo=TRUE)
computeItemsSampleGUI(x, method.select="K-means")
 

RclusTool documentation built on Aug. 29, 2022, 9:07 a.m.