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High-throughput sequencing allows the detection and quantification offrequencies of somatic single nucleotide variants (SNV) in heterogeneous tumorcell populations. In some cases, the evolutionary history and populationfrequency of the subclonal lineages of tumor cells present in the sample can bereconstructed from these SNV frequency measurements. However, automated methodsto do this reconstruction are not available and the conditions under whichreconstruction is possible have not been described.  We describe the conditions under which the evolutionary history can beuniquely reconstructed from SNV frequencies from single or multiple samplesfrom the tumor population and we introduce a new statistical model, PhyloSub,that infers the phylogeny and genotype of the major subclonal lineagesrepresented in the population of cancer cells. It uses a Bayesian nonparametricprior over trees that groups SNVs into major subclonal lineages andautomatically estimates the number of lineages and their ancestry. We samplefrom the joint posterior distribution over trees to identify evolutionaryhistories and cell population frequencies that have the highest probability ofgenerating the observed SNV frequency data. When multiple phylogenies areconsistent with a given set of SNV frequencies, PhyloSub represents theuncertainty in the tumor phylogeny using a partial order plot. Experiments on asimulated dataset and two real datasets comprising tumor samples from acutemyeloid leukemia and chronic lymphocytic leukemia patients demonstrate thatPhyloSub can infer both linear (or chain) and branching lineages and itsinferences are in good agreement with ground truth, where it is available.

Inferring clonal evolution of tumors from single nucleotide somatic mutations