clusterComp: Create components necessary for clustering

In Scavetta/complexomics: Complexome Profiling Analysis package

Create components necessary for clustering

Description

Reformat the table for the one neccessary for assignClusters function. Calculate the distance matirx using selected variant of correlation.

Usage

clusterComp(.df, scenar = "A", PearsCor = "centered")

Arguments

.df	data frame, table of normalised protein values
scenar	character, scenario intended for clustering, either "A" or "B"
PearsCor	character, pearsons correlation variant (centered/uncentered)

Value

list of data frames

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")

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