bio <- read.csv("ppg2008.csv", sep=",")
bio <- bio[order(bio$PTS),]
row.names(bio) <- bio$Name
bio <- bio[,2:20]
bio_matrix <- data.matrix(bio)
bio_heatmap <- heatmap(bio_matrix, Rowv=NA, Colv=NA, col = brewer.pal(9, "Blues"), scale="column", margins=c(5,10))
##
#Sample DATA
#Name ,G,MIN,PTS,FGM,FGA,FGP,FTM,FTA,FTP,3PM,3PA,3PP,ORB,DRB,TRB,AST,STL,BLK,TO,PF
#Genome1 ,79,38.6,30.2,10.8,22,0.491,7.5,9.8,0.765,1.1,3.5,0.317,1.1,3.9,5,7.5,2.2,1.3,3.4,2.3
#Genome2 ,81,37.7,28.4,9.7,19.9,0.489,7.3,9.4,0.78,1.6,4.7,0.344,1.3,6.3,7.6,7.2,1.7,1.1,3,1.7
#Genome3,82,36.2,26.8,9.8,20.9,0.467,5.9,6.9,0.856,1.4,4.1,0.351,1.1,4.1,5.2,4.9,1.5,0.5,2.6,2.3
library(ggplot2)
bio <- read.csv("seeTNF_Final", sep="\t")
row.names(bio) <- bio$Contig
bio <- bio[,2:256]
data=as.matrix(bio)
head(data)
#Rcolorbrewer palette
library(RColorBrewer)
coul = colorRampPalette(brewer.pal(8, "PiYG"))(25)
#heatmap(data)
# Use 'scale' to normalize (right)
heatmap(data, scale="column")
#heatmap(data, scale="column", col = coul)
