Abstract
BackgroundCancer progression reconstruction is an important development stemming from the phylogenetics field. In this context, the reconstruction of the phylogeny representing the evolutionary history presents some peculiar aspects that depend on the technology used to obtain the data to analyze: Single Cell DNA Sequencing data have great specificity, but are affected by moderate false negative and missing value rates. Moreover, there has been some recent evidence of back mutations in cancer: this phenomenon is currently widely ignored.ResultsWe present a new tool, gpps, that reconstructs a tumor phylogeny from Single Cell Sequencing data, allowing each mutation to be lost at most a fixed number of times. The General Parsimony Phylogeny from Single cell (gpps) tool is open source and available at https://github.com/AlgoLab/gpps.Conclusionsgpps provides new insights to the analysis of intra-tumor heterogeneity by proposing a new progression model to the field of cancer phylogeny reconstruction on Single Cell data.
Highlights
Cancer progression reconstruction is an important development stemming from the phylogenetics field
In this paper we propose gpps, an approach which combines Integer Linear Programming (ILP) with a Hill Climbing approach to infer a tumor progression that can include a limited amount of mutation losses, from single cell Deoxyribonucleic acid (DNA) sequencing data
Once again gpps correctly infers the clonal history proposed in the sequecing study; it correctly infers the placement of the driver mutations of the four
Summary
Cancer progression reconstruction is an important development stemming from the phylogenetics field. Ciccolella et al BMC Bioinformatics 2020, 21(Suppl 1):413 This is an important difference from cancer progression reconstruction, as in this case, we usually have data from all possible species (or better, from the conceptual analogs of species, that is clones). The clonal theory of cancer [2] postulates that a cancer consists of several clones, that is families of cells carrying the same mutations, that are subject to selective pressure resulting in clonal expansions In this case, clones play the same role as species in classical phylogenetics. The easiest way to obtain cancer data from a patient is via a biopsy, where samples from a tumor are extracted, typically using bulk DNA sequencing This procedure is fairly cheap, but the samples obtained are not very specific: the cells in a bulk-sequencing sample usually belong to several clones. Given a sufficiently large coverage, the error is small, and the procedure to obtain the data is standard and quite cheap
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