nsastarter.blogg.se

#If the last statement returns TRUE, all genes have passed the cuts. Gsg = goodSamplesGenes(datExpr, verbose = 3) # Run this to check if there are gene outliers # Manipulate file so it matches the format WGCNA needsĭatExpr = as.ame(t(datExpr)) # now samples are rows and genes are columnsĭim(datExpr) # 48 samples and 1000 genes (you will have many more genes in reality) Head(datExpr) # You see that genes are listed in a column named "X" and samples are in columns # This creates an object called "datExpr" that contains the normalized counts file output from DESeq2ĭatExpr = read.csv("SampleTimeSeriesRLD.csv") # Uploading data into R and formatting it for WGCNA

# Load WGCNA and flashClust libraries every time you open R # Only run the following commands once to install flashClust if needed