assignClusters: Create a data frames with cluster assignment

In Scavetta/complexomics: Complexome Profiling Analysis package

Create a data frames with cluster assignment

Description

This function creates a data frame with column specifying clusters assigned ot each protein using the table and distance matrix produced by clusterComp() function.

Usage

assignClusters(.listDf, sample, method = "complete", cutoff = 0.5)

Arguments

.listDf	list of data frames produced by clusterComp() function
sample	which of the two samples you want to apply the function to (labeled/unlabeled).
method	character, One of 'average', 'single' or 'complete' (default), specifies the linkage method to be used inside R hclust() function
cutoff	numeric, specifies the h value in R cutree() function, height at which to 'cut the tree', everything with distance below this value is assigned into same cluster everything with larger distance is in a different cluster extreme possible values are 0 to 2 (might not be reached for all data sets)

Value

dataframe

See Also

clusterComp

Examples

##Use example normalised proteins file
inputFile <- system.file("extData", "dataNormProts.txt", package = "ComPrAn")
#read file in and change structure of table to required format
forAnalysis <- protImportForAnalysis(inputFile)
# create components necessary for clustering
clusteringDF <- clusterComp(forAnalysis,scenar = "A", PearsCor = "centered")
#assign clusters
labTab_clust <- assignClusters(.listDf = clusteringDF,sample = "labeled",
method = 'complete', cutoff = 0.5)
unlabTab_clust <- assignClusters(.listDf = clusteringDF,sample = "unlabeled",
                               method = 'complete', cutoff = 0.5)

Scavetta/complexomics documentation built on Oct. 1, 2022, 2:15 a.m.