Abstract: Context: No efficient method is available to compare multi-locus estimates of diversity while taking into account inter-locus and inter-population stochastic variance. The advent of genome scan approaches makes the development of such tests absolutely necessary. Aims: We developed a method to compare genome-wide diversity estimates while taking into account – and factoring out – variation in census size and making use of inter-locus variance to assess significance of differences in diversity levels. Methods: An approach based on rarefaction with bootstrap re-sampling (RaBoT) was implemented into a test of multi-locus comparison of diversity coded in R. The properties of the test were studied by applying it to simulated populations with varying diversity levels and varying differences in diversity levels. The test was then applied to empirical data from disturbed and undisturbed populations of Virola michelii (Myristicaceae) genotyped at 693 amplified fragment length polymorphism (AFLP) markers. Results: RaBoT was found to be rather conservative, with large numbers of false negatives when the diversity in the compared populations was similar, and false positives mostly associated to comparisons of populations with extremely high levels of diversity. When applied to empirical data, RaBoT detected higher genetic diversity in a post-disturbance than in an undisturbed population and lower genetic diversity in a seedling than in the corresponding adult population, but it also revealed differences in diversity between subgroups within the disturbed and undisturbed plots. Conclusion: RaBoT is a sensitive method to compare multi-locus levels of diversity that can be applied both at the genotype level for dominant markers (e.g. AFLP) and at the allele level for biallelic codominant markers (e.g. single-nucleotide polymorphisms). © 2013 INRA and Springer-Verlag France.