View source: R/makeBarPlotClusterSummary.R
| makeBarPlotClusterSummary | R Documentation |
Title
makeBarPlotClusterSummary(df, name = "sample 1")
df |
data frame, contains columns: 'Protein Group Accessions' character 'Protein Descriptions' character isLabel character ('TRUE'/'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 |
name |
character, specifies the name of the sample |
plot
##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 bar plots for labeled and unlabeled samples
makeBarPlotClusterSummary(labTab_clust, name = 'labeled')
makeBarPlotClusterSummary(unlabTab_clust, name = 'unlabeled')
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