Structural variation in the human genome can be discovered by comparing paired-end next-generation sequencing reads from an individual to the human reference genome. Hormozdiari et al. improve the accuracy of discovering variants in repetitive regions of the genome through simultaneous analysis of several genomes, rather than the one-by-one approach that has been the norm. The key to discovering structural variants lies in the identification of 'discordantly mapped' paired-end reads: pairs that match regions in the reference that are further apart or closer together than expected are indicative of an insertion or deletion, respectively. Existing approaches fall short in repetitive genomic regions when there are several possible discordant mappings for a read pair, indicative of several possible variants. Hormozdiari et al. describe algorithms, called CommonLAW, that harness discordant read pairs from multiple genomes to determine which of the discordant mappings is most likely. Applying the new algorithms to genomes sequenced in the 1000 Genomes Project reduced the number of false-positive calls of mobile element insertions by >20-fold and provided moderate improvements to calling deletions. (Genome Res. published online, doi:10.1101/gr.120501.111, 2 November 2011)