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# Only run the following commands once to install WGCNA and flashClust onif your computerneeded
#install.packages("flashClust") 


# Load WGCNA and flashClust libraries every time you open R
library(WGCNA)
library(flashClust)


# Uploading data into R and formatting it for WGCNA 
# This creates an object called "datExpr" that contains the normalized counts file output from DESeq2
datExpr = read.csv("SampleTimeSeriesRLD.csv")
# "head" the file to preview it
head(datExpr) # You see that genes are listed in a column named "X" and samples are in columns


# Manipulate file so it matches the format WGCNA needs 
row.names(datExpr) = datExpr$X
datExpr$X = NULL
datExpr = as.data.frame(t(datExpr)) # now samples are rows and genes are columns
dim(datExpr) # 48 samples and 1000 genes (you will have many more genes in reality)


# Run this to check if there are gene outliers
gsg = goodSamplesGenes(datExpr, verbose = 3)
gsg$allOK 


#If the last statement returns TRUE, all genes have passed the cuts. If not, we remove the offending genes and samples from the data with the following:
#if (!gsg$allOK)
#	{if (sum(!gsg$goodGenes)>0)
#		printFlush(paste("Removing genes:", paste(names(datExpr)[!gsg$goodGenes], collapse= ", ")));
#		if (sum(!gsg$goodSamples)>0)
#			printFlush(paste("Removing samples:", paste(rownames(datExpr)[!gsg$goodSamples], collapse=", ")))
#		datExpr= datExpr[gsg$goodSamples, gsg$goodGenes]
#		}


#Create an object called "datTraits" that contains your trait data
datTraits = read.csv("Traits_23May2015.csv")
head(datTraits)
#form a data frame analogous to expression data that will hold the clinical traits.
rownames(datTraits) = datTraits$Sample
datTraits$Sample = NULL
table(rownames(datTraits)==rownames(datExpr)) #should return TRUE if datasets align correctly, otherwise your names are out of order
head(datTraits)


# You have finished uploading and formatting expression and trait data
# Expression data is in datExpr, corresponding traits are datTraits


save(datExpr, datTraits, file="SamplesAndTraits.RData")
#load("SamplesAndTraits.RData")