computeItems: Prediction of number of cells in colonies

Description Usage Arguments Details Value See Also Examples

Description

Apply a specific predictive model for counting of number of cells in colonies for each cluster.

Usage

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computeItems(data.sample, method, cluster, modelFile)

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

computeItems 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

itemsModel, countItems

Examples

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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, dir.save=tempdir())

x <- computeUnSupervised(x, K=3, method.name="K-means")
x <- computeItems(x, method="K-means", cluster="Cluster 1", modelFile)

RclusTool documentation built on Feb. 4, 2020, 5:08 p.m.