computeItemsSample {RclusTool} | R Documentation |
Prediction of number of cells in colonies
Description
Apply a specific predictive model for counting of number of cells in colonies for each cluster.
Usage
computeItemsSample(data.sample, method, cluster, modelFile = NULL)
Arguments
data.sample |
list containing features, profiles and clustering results. |
method |
character vector specifying the name of the clustering result to use. |
cluster |
character vector specifying the name of the cluster to consider for the application of the specific model. |
modelFile |
character vector specifying the path and the name of the RData model file. |
Details
computeItemsSample applies a specific predictive model for counting of number of cells in colonies for each cluster
Value
data.sample list containing features, profiles and clustering results with the number of cells for each particle.
See Also
Examples
dat <- rbind(matrix(rnorm(100, mean = 2, sd = 0.3), ncol = 2),
matrix(rnorm(100, mean = 4, sd = 0.3), ncol = 2),
matrix(rnorm(100, mean = 6, sd = 0.3), ncol = 2))
colnames(dat) <- c("x","y")
tf <- tempfile()
write.table(dat, tf, sep=",", dec=".")
x <- importSample(file.features=tf)
x <- computeUnSupervised(x, K=3, method.name="K-means")
x <- computeItemsSample(x, method="K-means", cluster="Cluster 1", modelFile=NULL)# to be fixed !
[Package RclusTool version 0.91.6 Index]