Congratulations to Nuria for passing with honors her Ph.D. viva!
Monica Valecha (India) and Fabián Crespo (Cuba/Ecuador) just arrived to start as PhD students in the CONTRA Marie Curie Innovative Training Network on Computational Oncology. They are going to work on different aspects of cancer evolution.
Welcome to the lab!.
Now we have people from three continents!
Posted in Lab, People
Congratulations to Merly for her PhD awarded today on NGS phylogenomics! You’ve been a GREAT student. Good luck for your postdoc at UC Santa Cruz. We’ll miss you…
New paper just out @GenomeMedicine! We report the impact of sequencing depth (and sampling effort) towards variant detection, genotype accuracy, clonal inference and phylogenetic reconstruction from single-cell cancer data.
NGSphy, our tool for simulating NGS reads along gene trees or genome-wide along a species tree with multiple gene families, is now published in Bioinformatics.
Source code, full documentation, and tutorials including a “Getting started” guide are available at http://github.com/merlyescalona/ngsphy
Both stability-constrained and structure-constrained substitution models are required to realistically predict the effect of mutations during protein evolution. A great study with Ugo Bastolla’s lab just published in Molecular Biology and Evolution,
Congratulations Iria for publishing a very nice paper describing the assembly of the genome of a beautiful angelfish!
Two open Marie Curie PhD positions (CONTRA ITN) in computational cancer evolution at our lab. Please apply!
ESR 11: Estimation of tumour growth rates from NGS data
Understanding the process of tumour growth is fundamental for many aspects of cancer biology. In this ESR project we will develop methods for the estimation of growth rates from single-cell and bulk NGS data. The main complication foreseen is that different selective regimes and neutral demographics can be easily confounded in particular considering the lack of genetic recombination.
ESR 12: Mutational patterns and models within tumours
Cancer data shows distinct genomic mutation rates that often are context-dependent and can be specific of distinct cancer types (“mutational signatures”). In this project we will try to understand in more detail how and which point mutations accumulate in cancer genomes within single patients, and using both single-cell and bulk NGS data. In this context, we will explore different models and their statistical fit in time and space, in relationship to cancer subtypes and progression, in bulk and single-cell NGS data.
CONTRA is an EU funded Innovative Training Network consisting of 8 principal investigators from equally many major European universities (see below) as well as partners from pharmaceutical, biotech-start up, and software development companies. CONTRA will hire 15 PhD students, each located and supervised at one of the participating universities. CONTRA will provide training in computational cancer research and professional software development, for analysis of novel experimental data including but not limited to single-cell genomics data.