plot_simdensity | R Documentation |
This function draws similarity values across all comparisons. Then, the best value obtained for the sample of interest is plotted to see how probable is to get this similarity value
plot_simdensity(measures, method)
measures |
dataframe with similarity metrics of comparisons between the sample of interest and the rest of cell lines included in the dataset |
method |
similarity metric to use for plotting. Options are pearson, manhattan, euclidean, and cosine |
A density plot with the distribution of similarities including the best similarity value obtained for the sample of interest. The min and max values are also reported
## Not run: posBins<-lapply(seq_len(22),function(chr) getBinsStartsEnds(window=500000, chr, lengthChr[chr])) ccle_cn<-getCNbins(posBins=posBins, data=cells_segcn, samples=unique(cells_segcn$sample)[1:2]) exp_cell<-as.matrix(ccle_cn[,1]) colnames(exp_cell)<-unique(cells_segcn$sample)[1] measures<-getSimilarities(dat1=exp_cell,dat2=ccle_cn) plot_simdensity(measures,method="pearson") ## End(Not run)
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