mkatari-bioinformatics-august-2013-clustering
Differences
This shows you the differences between two versions of the page.
| Both sides previous revisionPrevious revision | Next revisionBoth sides next revision | ||
| mkatari-bioinformatics-august-2013-clustering [2013/10/09 13:31] – mkatari | mkatari-bioinformatics-august-2013-clustering [2013/10/11 14:59] – mkatari | ||
|---|---|---|---|
| Line 36: | Line 36: | ||
| < | < | ||
| sigGenes.hclust.k2< | sigGenes.hclust.k2< | ||
| + | </ | ||
| + | |||
| + | Now to get all the genes that are in cluster 2 simply type. | ||
| + | |||
| + | < | ||
| + | hclust.k2.cluster2=names(which(sigGenes.hclust.k2==2)) | ||
| + | </ | ||
| + | |||
| + | 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). | ||
| + | |||
| + | < | ||
| + | hclust.k2.cluster2.normalized = sigGenes.normalized[hclust.k2.cluster2, | ||
| </ | </ | ||
mkatari-bioinformatics-august-2013-clustering.txt · Last modified: 2015/06/17 13:26 by mkatari