View source: R/exportClusterAssignments.R
exportClusterAssignments | R Documentation |
Covert clustered tables into format for export
exportClusterAssignments(labClustTable, unlabClustTable)
labClustTable |
output: data frame containing columns: 'Protein Group Accessions' character 'Protein Descriptions' character 'Cluster number - unlabeled' integer 'Cluster number - labeled' integer |
unlabClustTable |
labClustTable, unlabClustTable: data frames, contain columns: 'Protein Group Accessions' character 'Protein Descriptions' character isLabel character ('TRUE'/'FALSE') - here in one data frame all are TRUE in second one all are FALSE columns 1 to n, numeric, n is the total number of fractions/slices, each of this columns contains 'Precursor Area' values in a given fraction(columns) for a protein(rows) cluster integer |
dataframe
##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) #make table of cluster assginment tableClusterExport <- exportClusterAssignments(labTab_clust,unlabTab_clust)
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