Fig. 3

Performance analysis in presence of sampling distortion. Effect of sampling distortion on V-measure index (panel a) and mean absolute error of cellular prevalences (panel b) across multiple values for the total number of single cells (specified on top of each panel). Each box plot represents 10 simulated datasets each with 10 genotypes and 48 genomic loci. The cells are sampled from a Dirichlet-multinomial distribution with sample size m∈{50,100,200,500,1000} and parameters equal to the true prevalence of each genotype scaled by the concentration coefficient λ. The larger the λ, the closer the Dirichlet-multinomial distribution approximates the multinomial distribution. At higher values of λ the sampled cells better represent the true proportions of genotypes. Estimated values of λ for the real datasets are annotated on panel (b). We note that OncoNEM did not converge when number of cells exceeded 100 (boxes marked by a star). This result suggests that ddClone’s clustering and cellular prevalence estimates are fairly robust to the presence of distorted single cell sampling