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Scientific Fields
Diseases
Organisms
Applications
Technique
Date
19
Apr 2018
Time
14:00:00
Institut Pasteur, Rue du Docteur Roux, Paris, France
Address
Building: Francois Jacob -BIME Room: Auditorium Francois JACOB
Location
2018-04-19 14:00:00 2018-04-19 15:00:00 Europe/Paris C3BI Seminar: Learning tumor phylogenies from single-cell data by Niko Beerenwinkel Cancer progression is an evolutionary process characterized by the accumulation of mutations and responsible for tumor growth, clinical progression, and drug resistance development. We discuss how to reconstruct the evolutionary history of a tumor […] Institut Pasteur, Rue du Docteur Roux, Paris, France Christophe Becavin christophe.becavin@pasteur.fr

About

Cancer progression is an evolutionary process characterized by the accumulation of mutations and responsible for tumor growth, clinical progression, and drug resistance development. We discuss how to reconstruct the evolutionary history of a tumor from single-cell sequencing data. The tumor phylogeny problem is challenging because of sequencing errors and the high rate of allelic drop-out in single cell DNA sequencing experiments. We present a probabilistic model and a Markov Chain Monte Carlo approach to learn tumor phylogenies from such data. We use the model to develop a statistical test of the infinite sites assumption, which is frequently made in cancer evolution. We find that the infinite sites assumption is often violated by back mutations and sometimes also by parallel mutations.

Location

Building: Francois Jacob -BIME
Room: Auditorium Francois JACOB
Address: Institut Pasteur, Rue du Docteur Roux, Paris, France