Hi,

I'm currently using SomaticSignatures package to extract signatures from my NGS datas. 

I wanted to compare it to validated mutational signatures published by Alexandrov et al. (ALEXANDROV, Ludmil B., NIK-ZAINAL, Serena, WEDGE, David C., et al. Signatures of mutational processes in human cancer. Nature, 2013.) , to evaluate the implication of each validated profile in my datas. 

I got their profiles on their server (ftp://ftp.sanger.ac.uk/pub/cancer/AlexandrovEtAl) and included them in the matrix obtained from mutationContextMatrix function (= sca_occurence in tutorial).
Then I applied the 3 statistical methods (nmf, pca and kmeans). But the tool pools and calculates again all the mutational profiles.

 Is there a method to fix validated profiles and just having an estimation of their implication in my datas?

Thanks

The next release of the SomaticSignatures package contains the 21 mutational signatures of the Alexandrov paper as a data set. This version will be part of the upcoming Bioconductor release which will come out this month.

Currently, I am not aware of a stable out-of-the-box method for identifying a set of signatures in the observed data.  I have been working on this over the last months.  This will need further testing, and I expect to included them officially in the package soon (this fall or winter).

Thanks for your response. I look forward to the next version!

I also read in a paper (http://www.nature.com/ng/journal/v47/n7/full/ng.3335.html) by Katenin et al, in the methods section - mutation signature analysis, They compare their signature to Alexaddrov using Kullback-leibler divergence. Maybe this a viable way to compare.

From the paper

"The final signatures were extracted as in Alexandrov et al. This process yielded three mutational signatures. The signatures p obtained were compared to the published signatures q of Alexandrovet al. by mean Kullback-Leibler divergence (DKL(p||q) + DKL(q||p) ]/2."