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BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogenies.

Yuan K, Sakoparnig T, Markowetz F, Beerenwinkel N - Genome Biol. (2015)

Bottom Line: Here, we present BitPhylogenyBitPhylogeny, a probabilistic framework to reconstruct intra-tumor evolutionary pathways.Using a full Bayesian approach, we jointly estimate the number and composition of clones in the sample as well as the most likely tree connecting them.We validate our approach in the controlled setting of a simulation study and compare it against several competing methods.

View Article: PubMed Central - PubMed

ABSTRACT
Cancer has long been understood as a somatic evolutionary process, but many details of tumor progression remain elusive. Here, we present BitPhylogenyBitPhylogeny, a probabilistic framework to reconstruct intra-tumor evolutionary pathways. Using a full Bayesian approach, we jointly estimate the number and composition of clones in the sample as well as the most likely tree connecting them. We validate our approach in the controlled setting of a simulation study and compare it against several competing methods. In two case studies, we demonstrate how BitPhylogeny BitPhylogeny reconstructs tumor phylogenies from methylation patterns in colon cancer and from single-cell exomes in myeloproliferative neoplasm.

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Reconstructed tree and mutation profiles from single-cell exome sequencing data.(A) Reconstructed phylogeny. Non-empty clones are labeled a through i followed by the number of cells they contain. The vertical distance represents the evolutionary distance between clones. (B) Estimated probabilities of six SNVs in key genes across all cells. The error bars summarize 50,000 MCMC samples and are color-coded according to clone membership.
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Fig7: Reconstructed tree and mutation profiles from single-cell exome sequencing data.(A) Reconstructed phylogeny. Non-empty clones are labeled a through i followed by the number of cells they contain. The vertical distance represents the evolutionary distance between clones. (B) Estimated probabilities of six SNVs in key genes across all cells. The error bars summarize 50,000 MCMC samples and are color-coded according to clone membership.

Mentions: Figure 7A presents the results of the BitPhylogeny analysis. It shows a tree structure with a major clone (labeled as clone c) containing 33 out of all 58 cells. This clone is the most progressed clone since it has the longest total branch length from the root clone. One distinct feature of the reconstructed tree is that it captures both clonal progression (e.g., clone b to c) and binary branching with unobserved common ancestors (e.g., clones d and e). As a validation, genotypes from both bulk-sequenced normal and cancer cells are included in the analysis. The normal genotype is correctly identified as the root of the tree (clone a in Figure 7A). The genotype of the bulk-sequenced tumor is assigned to the most progressed clone c. While the analysis of the data with classical phylogenetic models in the original study only showed evidence for monoclonal evolution, BitPhylogeny reveals an additional structure of the tumor phylogeny involving in total half of all cells analyzed.Figure 7


BitPhylogeny: a probabilistic framework for reconstructing intra-tumor phylogenies.

Yuan K, Sakoparnig T, Markowetz F, Beerenwinkel N - Genome Biol. (2015)

Reconstructed tree and mutation profiles from single-cell exome sequencing data.(A) Reconstructed phylogeny. Non-empty clones are labeled a through i followed by the number of cells they contain. The vertical distance represents the evolutionary distance between clones. (B) Estimated probabilities of six SNVs in key genes across all cells. The error bars summarize 50,000 MCMC samples and are color-coded according to clone membership.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4359483&req=5

Fig7: Reconstructed tree and mutation profiles from single-cell exome sequencing data.(A) Reconstructed phylogeny. Non-empty clones are labeled a through i followed by the number of cells they contain. The vertical distance represents the evolutionary distance between clones. (B) Estimated probabilities of six SNVs in key genes across all cells. The error bars summarize 50,000 MCMC samples and are color-coded according to clone membership.
Mentions: Figure 7A presents the results of the BitPhylogeny analysis. It shows a tree structure with a major clone (labeled as clone c) containing 33 out of all 58 cells. This clone is the most progressed clone since it has the longest total branch length from the root clone. One distinct feature of the reconstructed tree is that it captures both clonal progression (e.g., clone b to c) and binary branching with unobserved common ancestors (e.g., clones d and e). As a validation, genotypes from both bulk-sequenced normal and cancer cells are included in the analysis. The normal genotype is correctly identified as the root of the tree (clone a in Figure 7A). The genotype of the bulk-sequenced tumor is assigned to the most progressed clone c. While the analysis of the data with classical phylogenetic models in the original study only showed evidence for monoclonal evolution, BitPhylogeny reveals an additional structure of the tumor phylogeny involving in total half of all cells analyzed.Figure 7

Bottom Line: Here, we present BitPhylogenyBitPhylogeny, a probabilistic framework to reconstruct intra-tumor evolutionary pathways.Using a full Bayesian approach, we jointly estimate the number and composition of clones in the sample as well as the most likely tree connecting them.We validate our approach in the controlled setting of a simulation study and compare it against several competing methods.

View Article: PubMed Central - PubMed

ABSTRACT
Cancer has long been understood as a somatic evolutionary process, but many details of tumor progression remain elusive. Here, we present BitPhylogenyBitPhylogeny, a probabilistic framework to reconstruct intra-tumor evolutionary pathways. Using a full Bayesian approach, we jointly estimate the number and composition of clones in the sample as well as the most likely tree connecting them. We validate our approach in the controlled setting of a simulation study and compare it against several competing methods. In two case studies, we demonstrate how BitPhylogeny BitPhylogeny reconstructs tumor phylogenies from methylation patterns in colon cancer and from single-cell exomes in myeloproliferative neoplasm.

Show MeSH
Related in: MedlinePlus