clusterComp: Create components necessary for clustering

View source: R/clusterComp.R

clusterCompR Documentation

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/ComPrAn documentation built on Oct. 3, 2022, 1:08 a.m.