#gene expression (3'-targeted RNA-seq) for proteins that are differentially expressed between treatment groups
#RPKM for each CGID were summed across the isotigs that blasted to that CGID

setwd("/Users/emmatimminsschiffman/Documents/Dissertation/3' targeted illumina sequencing C. gigas/isotig RNA-Seq/compare with proteomics")

gene.pco2<-read.csv('genexp sig proteins pCO2.csv', header=T, row.names=1) 
gene.pco2<-gene.pco2+1
pco2.log<-data.trans(gene.pco2, method='log', plot=F)
pheatmap(pco2.log, cluster_rows=T, cluster_cols=T, clustering_distance_rows='euclidean', clustering_distance_cols='euclidean', clustering_method='average')

gene.lowms<-read.csv('genexp sig proteins lowms.csv', header=T, row.names=1)
gene.lowms<-gene.lowms+1
lowms.log<-data.trans(gene.lowms, method='log', plot=F)
pheatmap(lowms.log, cluster_rows=T, cluster_cols=T, clustering_distance_rows='euclidean', clustering_distance_cols='euclidean', clustering_method='average')

gene.highms<-read.csv('genexp sig proteins highms.csv', header=T, row.names=1)
gene.highms<-gene.highms+1
highms.log<-data.trans(gene.highms, method='log', plot=F)
pheatmap(highms.log, cluster_rows=T, cluster_cols=T, clustering_distance_rows='euclidean', clustering_distance_cols='euclidean', clustering_method='average')