Description Usage Arguments Value Examples
Function to select an optimal number of clusters and a model to be fitted during the EM phase of clustering for Gaussian Mixture Models. The function provides summaries and helps to visualise clusters based on Fi-score using scatter plotting and dimension reduction plots.
1 2 3 4 5 6 7 | cluster_ID(
pdb_df,
max_range = 20,
secondary_structures = TRUE,
clusters = NULL,
modelNames = NULL
)
|
pdb_df |
data frame containing processed PDB file with Fi-score values |
max_range |
number of clusters to consider during model selection; default 20 clusters |
secondary_structures |
include information on secondary structure elements from PDB when plotting, default value is TRUE |
clusters |
number of clusters to test not based on the best BIC output, user also needs to supply modelNames |
modelNames |
can only be supplied when clusters are also specified, this option will model based on the user parameters |
A data frame object that contains a summary of clusters
1 2 3 4 | path_to_processed_PDB<- system.file("extdata", "pdb_df.tabular", package="Fiscore")
# basic usage of cluster_ID
pdb_df<-read.table(path_to_processed_PDB)
head(cluster_ID(pdb_df))
|
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