Description Usage Arguments Examples
View source: R/cluster_param_selection.R
Calculates validation metrics for different clustering methods and different numbers of partitions. The validation metrics are plotted.
1 2 3 4 5 6 7 8 9 10 11 12 |
dataset |
A transcriptomics dataset. Preferably filtered first. First columns should be gene names. All other columns should be expression levels. |
distance |
A distance matrix. If a distance matrix has already been
created (such as by using the |
k |
A numeric vector giving the number of clusters to be evaluated. |
method |
The clustering method(s) to be used. Multiple methods can be considered by providing a character vector. Currently accepts 'pam', 'agglom' and 'diana'. |
metric |
The distance metric to be used to calculate the distances between genes. See parallelDist::parDist for all accepted arguments. Also allows the option of 'abs.correlation'. Not used if a distance matrix is provided. |
scale |
Logical. If TRUE then each gene will be scaled. |
nthreads |
The number of threads to be used for parallel computations. If NULL then the maximum number of threads available will be used. |
save.plot |
Logical. If TRUE then saves the plots generated. |
save.df |
Logical. If TRUE then saves the validation metric results as a .csv file. |
path |
The directory to be used for saving plots and the validation metric results to. Uses the name of the dataset object appended with '_validation' if this argument is not specified. |
1 2 3 | k.options <- seq(2,10)
hclust.validation <- ClusterParamSelection(Laurasmappings, k=k.options,
nthreads = 2)
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