We describe the use of a statistical model in a genome-wide microarray-based yeast genetic screen performed by imposing different genetic selections on thousands of yeast mutants in parallel. A mixture model is fitted to data obtained from oligonucleotide arrays hybridized to 20-mer oligonucleotide "barcodes'' and a procedure based on the fitted model is used to search for mutants differentially represented under experimental and control conditions. The fitted stochastic model provides a way to assess uncertainty. We demonstrate the usefulness of the model by applying it to the problem of screening for components of the nonhomologous end joining (NHEJ) pathway and identified known components of the NHEJ pathway.