Cisplatin, a frontline chemotherapy agent for ovarian, breast and lung cancers, is in a class of DNA damaging agents that lead to replication fork stalling and collapse, apoptosis and cell death. Cisplatin sensitivity is affected by a number of DNA repair pathways including nucleotide excision repair, the multiple pathways that collectively make up post replication repair, and processes that specifically incise DNA interstrand crosslinks. Although much is known about the genetic control of these DNA repair mechanisms, the interactions and overlapping functions of these pathways are not completely understood. Furthermore, efforts to catalog the genes affecting cellular sensitivity to cisplatin has either defined a few, well studied genes, or has defined a large number of genes that may only be peripherally involved in sensitivity. We therefore reexamined datasets of cisplatin sensitivity in Saccharomyces cerevisiae to define a gene set for systematic double mutant analysis. The CLIK (Cutoff Linked to Interaction Knowledge) algorithm expanded the number of likely cisplatin sensitive genes in individual high throughput studies, and additional genes were identified via growth curve analysis of gene disruption libraries using multiple cisplatin concentrations. Pilot experiments have highlighted the importance of tailoring the drug concentration for each query mutation to optimally identify epistatic versus synergistic genetic interactions. Analysis of a translesion polymerase, Polζ (Rev3-Rev7) and the homologous recombination related SHU complex (Shu1-Shu2-Psy3-Csm2) demonstrates that optimal detection of synergy between these complexes requires a low concentration of cisplatin. On the other hand, detection of epistasis among Polζ complex members requires a much lower concentration of cisplatin than the SHU complex. Interestingly, synergy was detected between SHU complex members Shu1 and Shu2, which suggests a possible redundancy between these two factors. These experiments lay the foundation for a high-fidelity cisplatin dependent epistasis map that will be used to disambiguate relationships between the many gene and pathways involved in managing DNA crosslinks.