And to that you add 1 single gene which is more expressed in samples 6-12, than in 1-6.
Let's say that you have 12 samples, so that all samples have the exact same expression level (say 12000 genes). * Can you cut your gene tree into 4 clusters? Explore the `pheatmap` function pressing tab. * Can you change the clustering to 'ward.D2'? Explore the `pheatmap` function pressing tab. * What does the 'scale' parameter mean? What happens with the clustering if we change it to 'none' or to 'columns'? Do they look familiar with the previous ones? * Check the dendrograms on the side of the heatmap. Pheatmap( data, scale = "row ", color = colorRampPalette(c( "navy ", "white ", "firebrick "))( 90), border_color = NA, cluster_cols = F) Load the sequencing data and the metadata data with sample information. Rafalib ::mypar( mar =c( 6, 2.5, 2.5, 1)) #sets nice arrangement for the whole document Library( pvclust) #clustering bootstrapping
Library( DESeq2) #differential gene expression for RNA-seq Create a directory named `data` in your current working directory for input and output files.
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