MEDICC — highly recommended!

It’s good to get feedback now and then. Better still if it is positive.

Ian Holmes highly recommends our paper introducing MEDICC (Minimum Event Distance for Intra-tumor Copy-number Comparisons; more here) at F1000:

High-throughput sequencing of tumors should be informative about the stages of cancer progression. This paper is one of several that exploit the interesting observation that cancer progression is essentially a phylogenetic reconstruction problem. Of course, that should not be surprising since cancer is an evolutionary disease.

This paper looks at copy number variation (CNV) in particular, reducing CNV to an integer vector by considering SNPs in a series of windows along the genome. It addresses both allele phasing and phylogeny.

Most interestingly, from a methodological viewpoint, it does so using techniques from language and automata theory (specifically, context-free grammars and finite-state transducers). These are both tools that have found application in phylogenetics, in fact, as rather advanced tools for modelling the evolution of things like indels and RNA structure.

So, this paper represents an example of the state-of-the-art in one field (phylogenetics) being applied to advance another (computational cancer biology).

Highly recommended!

Thank you. Very appreciated.

Florian

Reference:

• Schwarz RF, Trinh A, Sipos B, Brenton JD, Goldman N, Markowetz F.
  Phylogenetic quantification of intra-tumour heterogeneity.
  PLoS Comput Biol. 2014 Apr 17;10(4):e1003535.
  doi: 10.1371/journal.pcbi.1003535.  PMID: 24743184;