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mkatari-bioinformatics-august-2013-clustering [2013/10/09 13:31] mkatarimkatari-bioinformatics-august-2013-clustering [2013/10/11 15:01] mkatari
Line 36: Line 36:
 <code> <code>
 sigGenes.hclust.k2<-cutree(sigGenes.normalized.hclust, k=2) sigGenes.hclust.k2<-cutree(sigGenes.normalized.hclust, k=2)
 +</code>
 +
 +Now to get all the genes that are in cluster 2 simply type.
 +
 +<code>
 +hclust.k2.cluster2=names(which(sigGenes.hclust.k2==2))
 +</code>
 +
 +Now we can create a new matrix/data frame with just these genes. This new matrix can be used to plot a heatmap to make it easier to see a expression profile of the cluster (see below).
 +
 +<code>
 +hclust.k2.cluster2.normalized = sigGenes.normalized[hclust.k2.cluster2,]
 </code> </code>
  
Line 73: Line 85:
 </code> </code>
  
-Create heatmap. We can save it to a pdf file+Create heatmap. We can save it to a pdf file. Note that sigGenes.normalized is just a matrix. Here we can provide any matrix of values, for example hclust.k2.cluster2.normalized which is the expression values of genes in cluster 2 (see above)
  
 <code> <code>
mkatari-bioinformatics-august-2013-clustering.txt · Last modified: 2015/06/17 13:26 by mkatari