BACKGROUND: Multiplex-Dependent Probe Amplification (MLPA) is a cost-effective experimental method for candidate gene studies, aimed at the identification of copy number alterations. The analysis of such genetic variants, from electropherogram peak intensities, involves two main stages. First, peak normalization for each probe is required to remove the contribution of probe size to peak intensity. Second, the statistical significance of peak alteration between case and control samples is estimated. A number of methods have been proposed in each step with varying levels of complexity and precision. However, there is no single framework from which the results of each method and possible combinations at each step can be assessed. RESULTS: We present MLPAstats, an R package designed to integrate the methods for exploring different analysis scenarios in a reliable way. A GUI has been developed to allow researchers to find their optimal analysis strategy. CONCLUSIONS: MLPAstats is an analysis tool that promotes the use of cost-effective MLPA suitable for candidate gene studies. Its R implementation allows future methods to be easily incorporated, while its GUI will facilitate its use by non-expert analysts. A vignette describing a set-by-step tutorial is also available with the package.