I have a reference genome and now I would like to call structural variants from Illumina pair-end whole genome resequencing data (insert size 700bp). There are many tools for SV calls (I made an incomplete list of tools bellow). There is also a tool for merging SV calls from multiple methods / samples - SURVIVOR. Is there a combination of methods for SV detection with optimal balance between sensitivity and specificity?There is a benchmarking paper, evaluating sensitivity and specificity of SV calls of individual methods using simulated pair-end reads. However, there is no elaboration on the combination of methods.List of tools for calling structural variants:LumpyBreakDancerMantaDellyGRIDSSMeerkatPindelSoftsvPrism
How can I call structural variants (SVs) from pair-end short read resequencing data?
ngs;structural variation;variant calling
I think the best method or combination of methods will depend on aspects of the data that might vary from one dataset to another. E.g. the type, size, and frequency of structural variants, the number SNVs, the quality of the reference, contaminants or other issues (e.g. read quality, sequencing errors) etc.For that reason, I'd take two approaches:Try a lot of methods, and look at their overlapValidate a subset of calls from different methods by wet lab experiments - in the end this is the only real way of knowing the accuracy for a particular case.