MLGsim: a program for detecting clones using a simulation approach

Sexual and asexual forms of plants and animals often coexist in the same population. In such cases, the assessment of genotypic identity among individuals is vital for valid biological interpretation of population and evolutionary processes. Several methods are used for identifying clones based on genetical marker data. The only method that detects which multilocus genotypes are likely to be clones has limitations in statistical power. We present a program (MLGSim) that, using a simulation approach, calculates significance values for the likelihood that a multilocus genotype observed more than once in a population is the result of sexual reproduction.