Fig. 1

a A tumour phylogeny describes the order of accumulation of somatic mutations, CNAs, epigenetic modifications, etc. in a single tumour. The model generates a set of possible genotypes, which are observed with an unknown spatial and density distribution in a tumour (primary and metastases). b Multi-region bulk sequencing returns a mixed signal from different tumour subpopulations, with potential contamination of non-tumour cells (not shown) and symmetric rates of false positives and negatives in the calling. Thus, a sample will harbour lesions from different tumour lineages, creating spurious correlations in the data. c If we sequence genomes of single cells we can, in principle, have a precise signal from each subpopulation. However, the inference with these data is made harder by high levels of asymmetric noise, errors in the calling and missing data. d Different scenarios of tumour evolution can be investigated via TRaIT. (i) Branching evolution (which includes linear evolution), (ii) Branching evolution with confounding factors annotated in the data, (iii) Models with multiple progressions due to polyclonal tumour origination, or to the presence tumour initiating event missing from input data