mkatari-bioinformatics-august-2013-clustering
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| mkatari-bioinformatics-august-2013-clustering [2014/12/11 14:16] – mkatari | mkatari-bioinformatics-august-2013-clustering [2014/12/11 14:41] – mkatari | ||
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| ====== K-means ====== | ====== K-means ====== | ||
| + | The K-means method uses euclidean distance to measure distance. Since in biology we are more interested in gene expression profiles instead of magnitude of expression levels, let's scale our data so that the mean of the expression values is 0 and the expression values will be the standard deviations away from the mean. | ||
| + | < | ||
| + | sigGenesMean = rowMeans(sigGenes.normalized) | ||
| + | sigGenesSD = apply(sigGenes.normalized, | ||
| + | </ | ||
| ====== Heatmap ====== | ====== Heatmap ====== | ||
mkatari-bioinformatics-august-2013-clustering.txt · Last modified: 2015/06/17 13:26 by mkatari