Subsampling
The inference method described above assumes that all individuals from
the in silico population have been sampled and genotyped. When
subsampling is applied in a realistic manner (i.e. , mimicking the
subsampling level of most studies in molecular ecology), however, real
issues emerge in terms of parameter accuracy and consequent estimates ofc .
Genetic parameters (which proved to be less informative for assessing
the clonal rate) were nearly unaffected by realistic sample sizes,
whereas genotypic parameters (which were most informative) were
considerably overestimated when using realistic sample sizes, leading to
a gross underestimate of c from real datasets collected from natural
populations. This situation remained nearly unchanged when subsampling
was performed before the population reached equilibrium (see Figure S2).
The R parameter is so susceptible to sampling bias that a
sampling effort of 50 units, consistent with many works studied thus
far, including ours, cannot reliably estimate an R value lower
than 0.9, with the exception of highly clonal populations
(c >0.8). A correct and unbiased estimate of R can be
achieved only by genotyping the entire population (Figures 4 and S2).
Interestingly, the variance in F IS computed from
samples provided more identifiable signals of rates of clonality at all
populations sizes than genotyping all individuals. However, away from
equilibrium, the variance in F IS became less
informative than that obtained at equilibrium (Figure S2).