mkatari-bioinformatics-august-2013-clustering
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mkatari-bioinformatics-august-2013-clustering [2014/12/11 14:55] – [K-means] mkatari | mkatari-bioinformatics-august-2013-clustering [2014/12/11 15:24] – [K-means] mkatari | ||
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scaledSigGenes = t(apply(sigGenes.normalized, | scaledSigGenes = t(apply(sigGenes.normalized, | ||
colnames(scaledSigGenes)=colnames(sigGenes.normalized) | colnames(scaledSigGenes)=colnames(sigGenes.normalized) | ||
+ | |||
+ | #now to run k-means, in this case we are starting with 2 cluster. | ||
+ | #just like for heirarchical clustering, we have to first transpose the data so compare genes. | ||
+ | |||
+ | SigGenes.kmeans.2 = kmeans(t(scaledSigGenes), | ||
+ | |||
+ | #a plot of the groups | ||
+ | plot(SigGenes.kmeans.2$centers[1, | ||
+ | |||
+ | # a measure of how well the clustering has performed | ||
+ | # it is the sum of squares between members of the outside group and sum of squares total | ||
+ | # higher the better. | ||
+ | SigGenes.kmeans.2$betweenss/ | ||
+ | |||
+ | #to get the genes in the different clusters | ||
+ | SigGenes.kmeans.2.group1 = names(which(SigGenes.kmeans.2$cluster==1)) | ||
+ | SigGenes.kmeans.2.group2 = names(which(SigGenes.kmeans.2$cluster==2)) | ||
</ | </ |
mkatari-bioinformatics-august-2013-clustering.txt · Last modified: 2015/06/17 13:26 by mkatari