Understanding DNA double-strand break (DSB) repair is crucial for the development of targeted anticancer therapies, yet the roles of many genes remain unclear. Recent studies show that disruption of known DSB repair genes can alter the sequence-specific distribution of mutations arising after DSB repair, suggesting that genome-wide perturbation screens could be leveraged to identify new DSB genes leading to distinct deviations from the expected wild-type distribution. Given the challenges of designing controls for a genome-wide screen, we explore the high gene throughput to forgo the use of traditional controls by reframing the analysis as an outlier detection problem, assuming that most genes have minimal influence on DSB repair outcomes. We propose MUSICiAn (Mutational Signature Catalogue Analysis), a compositional data analysis method that ranks gene perturbation impact on mutational spectra without controls by measuring deviations from the central tendency considering the distribution of all spectra. We show that MUSICiAn effectively estimates pseudo-controls for the Repair-seq screen, yielding 476 genes and 60 nontargeting controls. We further apply MUSICiAn to the first genome-wide screen of 18 406 genes with mutational spectra readout, MUSIC, reporting that MUSICiAn successfully recovers known DSB repair genes, highlights the spliceosome as a lesser-appreciated player, and reveals candidates for further investigation.