We are analyzing https://link.springer.com/article/10.1186/1471-2105-15-35.

Title:
Inferring clonal evolution of tumors from single nucleotide somatic mutations | BMC Bioinformatics
Description:
Background High-throughput sequencing allows the detection and quantification of frequencies of somatic single nucleotide variants (SNV) in heterogeneous tumor cell populations. In some cases, the evolutionary history and population frequency of the subclonal lineages of tumor cells present in the sample can be reconstructed from these SNV frequency measurements. But automated methods to do this reconstruction are not available and the conditions under which reconstruction is possible have not been described. Results We describe the conditions under which the evolutionary history can be uniquely reconstructed from SNV frequencies from single or multiple samples from the tumor population and we introduce a new statistical model, PhyloSub, that infers the phylogeny and genotype of the major subclonal lineages represented in the population of cancer cells. It uses a Bayesian nonparametric prior over trees that groups SNVs into major subclonal lineages and automatically estimates the number of lineages and their ancestry. We sample from the joint posterior distribution over trees to identify evolutionary histories and cell population frequencies that have the highest probability of generating the observed SNV frequency data. When multiple phylogenies are consistent with a given set of SNV frequencies, PhyloSub represents the uncertainty in the tumor phylogeny using a “partial order plot”. Experiments on a simulated dataset and two real datasets comprising tumor samples from acute myeloid leukemia and chronic lymphocytic leukemia patients demonstrate that PhyloSub can infer both linear (or chain) and branching lineages and its inferences are in good agreement with ground truth, where it is available. Conclusions PhyloSub can be applied to frequencies of any “binary” somatic mutation, including SNVs as well as small insertions and deletions. The PhyloSub and partial order plot software is available from https://github.com/morrislab/phylosub/ .
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Keywords {🔍}

snv, frequencies, population, subclonal, snvs, tumor, model, tree, phylosub, samples, number, lineage, figure, sample, frequency, data, lineages, multiple, pubmed, article, google, scholar, single, process, posterior, set, sequencing, prior, distribution, clonal, cells, order, structure, phylogeny, evolutionary, file, partial, dirichlet, plot, read, full, phylogenies, node, algorithm, evolution, probability, chain, copy, authors, genotype,

Topics {✒️}

tree-structured stick-breaking process open access article tree-structured stick breaking complete-data log likelihood layered stick-breaking construction complete-data likelihood trace highest complete-data likelihood high-throughput sequencing methods acute myeloid leukemia hematopoietic stem cells single-cell dna sequencing single nucleotide variants graph-based clustering algorithm single-cell assay agree 𝑎 𝑖 𝑡 stick-breaking process bmc bioinformatics 15 article download pdf inferring intra-tumor heterogeneity chronic lymphocytic leukemia pseudo-count parameters full size image 𝜇 𝑖 𝑟 somatic dna alterations privacy choices/manage cookies allelic count data read count probabilities 𝜇 𝑖 𝑣 stick-breaking processes highly heterogeneous population stick-breaking construction [29] stick-breaking construction semi-manual reconstruction procedure related subjects inferring clonal evolution dirichlet process prior tet2-e1357stop lineage genotype recursively breaking sticks 𝜙 𝑧 𝑖 authors’ original file �binary” somatic mutation article jiao ontario research fund 𝜇 𝑖 aa 𝜇 𝑖 ab 𝜇 𝑖 bb early researcher award quaid morris metropolis-hastings algorithm deep-targeted sequencing

Questions {❓}

Marusyk A, Almendro V, Polyak K: Intra-tumour heterogeneity: A looking glass for cancer?
Edu/viewdoc/summary?

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WebPage:
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         headline:Inferring clonal evolution of tumors from single nucleotide somatic mutations
         description:High-throughput sequencing allows the detection and quantification of frequencies of somatic single nucleotide variants (SNV) in heterogeneous tumor cell populations. In some cases, the evolutionary history and population frequency of the subclonal lineages of tumor cells present in the sample can be reconstructed from these SNV frequency measurements. But automated methods to do this reconstruction are not available and the conditions under which reconstruction is possible have not been described. We describe the conditions under which the evolutionary history can be uniquely reconstructed from SNV frequencies from single or multiple samples from the tumor population and we introduce a new statistical model, PhyloSub, that infers the phylogeny and genotype of the major subclonal lineages represented in the population of cancer cells. It uses a Bayesian nonparametric prior over trees that groups SNVs into major subclonal lineages and automatically estimates the number of lineages and their ancestry. We sample from the joint posterior distribution over trees to identify evolutionary histories and cell population frequencies that have the highest probability of generating the observed SNV frequency data. When multiple phylogenies are consistent with a given set of SNV frequencies, PhyloSub represents the uncertainty in the tumor phylogeny using a “partial order plot”. Experiments on a simulated dataset and two real datasets comprising tumor samples from acute myeloid leukemia and chronic lymphocytic leukemia patients demonstrate that PhyloSub can infer both linear (or chain) and branching lineages and its inferences are in good agreement with ground truth, where it is available. PhyloSub can be applied to frequencies of any “binary” somatic mutation, including SNVs as well as small insertions and deletions. The PhyloSub and partial order plot software is available from https://github.com/morrislab/phylosub/ .
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         Dirichlet Process
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         Microarrays
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         Computer Appl. in Life Sciences
         Algorithms
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