Clustering output generated by: QC_output<-One_step_clustering(SNV_list = Input_Example,contamination = c(0,0), nclone_range = 2:5,maxit = 1, save_plot = FALSE,ncores = 1, epsilon = 0.01) On October, 30th 2015
list of lists
Results of Expectation maximization: *fik: probability of a mutation (line) to belong to clone k (column) *weights: proportion of mutations belonging to clone k *centers: cellularity of clone k in sample j *val: value of log-likelihood
input data without mutations removed (missing genotype or genotype not AB if filtered on AB)
Result of hard clustering: each mutation is attributed to a single clone
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