Fig. 11
Analysis results of an acute lymphoblastic leukemia (ALL) dataset [12]. Analysis results of a patient with ALL (Patient 1) [12]. The variant allele frequencies (VAFs) from the bulk data (panel a, top) along with the consensus genotypes estimated from the binary cell matrix (panel A, bottom). These two constitute the input to the ddClone model. We note that the binary cell matrix b is displayed here for comparison and is not an input to ddClone. This binary cell matrix was used in [12] to cluster the cells into clones (vertical bar at the right side of the figure) and consensus genotypes (bottom part of panel a). ddClone clusters mutations into 6 groups (panel c, top) and estimates cellular prevalence (Φ) for each (panel c, bottom). ddClone’s estimated Φ are highly correlated with the corrected bulk VAFs (R 2=0.98, also see Additional file 1), suggesting that it does not introduce unreasonable structure in the data. Furthermore, when there is evidence in the bulk, it can override its prior and split clusters as necessary. For instance, even though locus chr19:40895668 has the same prior genotype as loci in cluster 4, its VAF in the bulk data is 1.5 times that of the mean of loci in cluster 4. This hints at a finer structure in cluster 4, and ddClone has automatically assigned chr19:40895668 to a separate cluster