| gdcHeatmap {GDCRNATools} | R Documentation |
A heatmap showing unsupervised hierarchical clustering of
DE genes/miRNAs by heatmap.2 in the
gplots package
gdcHeatmap(deg.id, metadata, rna.expr)
deg.id |
a vector of Ensembl gene ids or miRBase v21 mature miRNA ids |
metadata |
metadata parsed from |
rna.expr |
|
A heatmap with rows are DE genes/miRNAs and columns are samples. Solid Tissue Normal samples are labeled with blue and Primary Tumor samples are labeled with red
Ruidong Li and Han Qu
genes <- c('ENSG00000000938','ENSG00000000971','ENSG00000001036',
'ENSG00000001084','ENSG00000001167','ENSG00000001460')
samples <- c('TCGA-2F-A9KO-01', 'TCGA-2F-A9KP-01',
'TCGA-2F-A9KQ-01', 'TCGA-2F-A9KR-01',
'TCGA-2F-A9KT-01', 'TCGA-2F-A9KW-01')
metaMatrix <- data.frame(sample_type=rep('PrimaryTumor',6),
sample=samples,
days_to_death=seq(100,600,100),
days_to_last_follow_up=rep(NA,6))
rnaExpr <- matrix(c(2.7,7.0,4.9,6.9,4.6,2.5,
0.5,2.5,5.7,6.5,4.9,3.8,
2.1,2.9,5.9,5.7,4.5,3.5,
2.7,5.9,4.5,5.8,5.2,3.0,
2.5,2.2,5.3,4.4,4.4,2.9,
2.4,3.8,6.2,3.8,3.8,4.2),6,6)
rownames(rnaExpr) <- genes
colnames(rnaExpr) <- samples
gdcHeatmap(deg.id=genes, metadata=metaMatrix, rna.expr=rnaExpr)