SIB Bioinformatics Awards 2019: Single-cell mutation identification via phylogenetic inference
Channel: SIB - Swiss Institute of Bioinformatics
Date: 2019-10-10

What you will discover: a model and method to identify mutations in single-cells using their phylogenetic relationship

Target audience: Scientists who analyze single-cell DNA sequencing data in basic research or clinical settings, e.g. bioinformaticians embedded in clinical research groups, staff of bioinformatics core units, etc.

Speaker: Jochen Singer, Bioinformatics Scientist, Novartis Pharma AG (see biography below)

Click to access specific sections of the talk:
• The problem with noisy data in tumor evolution 00:55
• Model and method overview 05:23
• Results on simulated data 09:08
• Results on a real data set from 16 cancer cells 10:43

Reference paper
Singer J et al. Single-cell mutation identification via phylogenetic inference. Nature communications 9, no. 1 (2018): 5144.  https://doi.org/10.1038/s41467-018-07627-7


Any question about this talk? Contact Jochen: jochen.singer@bsse.ethz.ch 

More about the speaker: 
Jochen studied bioinformatics and computational science in Berlin and Melbourne. Then he joined the Algorithmic Bioinformatics group in Berlin where he developed novel and efficient methods for high-throughput sequencing data. Afterwards, he moved to Switzerland and did his PhD in the Computational Biology Group at the ETH Zurich. Here he focused on the design and implementation of high-throughput sequencing analysis workflows and the development of statistical methods for mutation identification in single-cell experiments. After finishing his PhD in 2019, he started working as a Bioinformatics Scientist at Novartis.


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