ShixiangWang
commented
4 years ago Application of SigProfiler and SignatureAnalyzer to synthetic data Our goal was to evaluate SignatureAnalyzer and SigProfiler on realistic synthetic data to identify any potential limitations of these two methods. SignatureAnalyzer and SigProfiler were tested on 11 sets of synthetic data, encompassing a total of 64,400 synthetic samples, in which known signature profiles were used to generate catalogues of synthetic mutational spectra. We operationally defined ‘realistic’ data as those based on the characteristics of either SignatureAnalyzer’s or SigProfiler’s analysis of the PCAWG genome data. SignatureAnalyzer’s reference signature profiles were based on COMPOSITE signatures, consisting of 1,536 types of strand-agnostic SBSs in pentanucleotide context, 78 types of DBSs and 83 types of small indels, for a total of 1,697 mutation types. SigProfiler’s reference analysis was based on strand-agnostic SBSs in the context of one 5′ and one 3′ base. For each test, we generated two sets of realistic data: SigProfiler-realistic (based on SigProfiler’s reference signatures and attributions) and SignatureAnalyzer-realistic (based on SignatureAnalyzer’s reference signatures and attributions), as well as two other types of data that involved using SignatureAnalyzer profiles with SigProfiler attributions and vice versa. A detailed description of each of the 11 sets of synthetic data and the results from applying SigProfiler and SignatureAnalyzer are provided in Supplementary Note 2.
Construct a series of functions to do data simulation analysis
https://github.com/ShixiangWang/sigflow/issues/16