Difference between revisions of "2018 June Taeyoung Lab note"

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(pheatmap)
 
Line 9: Line 9:
  
 
             Gene        B        Y        G        I
 
             Gene        B        Y        G        I
1 Jatcu.01g001630  0.777053  0.900879  1.93941  4.831030
+
1 Jatcu.01g001630  0.777053  0.900879  1.93941  4.831030
2 Jatcu.02g000639  3.246920  3.148340 23.04090 35.914500
+
2 Jatcu.02g000639  3.246920  3.148340 23.04090 35.914500
3 Jatcu.02g000941 12.631700 13.201900 23.73470 14.621300
+
3 Jatcu.02g000941 12.631700 13.201900 23.73470 14.621300
4 Jatcu.02g000968  7.888650  3.338680  4.60163 10.876700
+
4 Jatcu.02g000968  7.888650  3.338680  4.60163 10.876700
5 Jatcu.02g001631  5.646930  7.952740  4.64940  5.600850
+
5 Jatcu.02g001631  5.646930  7.952740  4.64940  5.600850
6 Jatcu.03g000784  3.271440  3.703690  1.34210  0.956547
+
6 Jatcu.03g000784  3.271440  3.703690  1.34210  0.956547
  
 
  rownames(Data)=Data$Gene
 
  rownames(Data)=Data$Gene
 
  pheatmap(log(Data[2:5]+1),color = colorRampPalette(c("white","firebrick3"))(50),cluster_cols = FALSE, cluster_rows = FALSE)
 
  pheatmap(log(Data[2:5]+1),color = colorRampPalette(c("white","firebrick3"))(50),cluster_cols = FALSE, cluster_rows = FALSE)

Latest revision as of 04:33, 6 October 2018

UpSetR plot

library(UpSetR)
upset(Data,sets = c("Lus","Ptr","Rco","Jcu","Mes","Hbr"),order.by="freq",empty.intersections="on")

pheatmap

library(pheatmap)
Data<-read.table("PE_gene_list.txt.RPKM",header=T)
head(Data)
            Gene         B         Y        G         I
1 Jatcu.01g001630  0.777053  0.900879  1.93941  4.831030
2 Jatcu.02g000639  3.246920  3.148340 23.04090 35.914500
3 Jatcu.02g000941 12.631700 13.201900 23.73470 14.621300
4 Jatcu.02g000968  7.888650  3.338680  4.60163 10.876700
5 Jatcu.02g001631  5.646930  7.952740  4.64940  5.600850
6 Jatcu.03g000784  3.271440  3.703690  1.34210  0.956547
rownames(Data)=Data$Gene
pheatmap(log(Data[2:5]+1),color = colorRampPalette(c("white","firebrick3"))(50),cluster_cols = FALSE, cluster_rows = FALSE)