To identify the genomic regions that show highest genetic differentiation between Pygmy and non-Pygmy populations, we computed the informativeness for assignment (I n ) for each marker (Rosenberg et al. 2003).
For each pair of conspecific populations, we computed the ratio of sequence divergence (%SD) estimated from a 540 bp region of cytochrome b, to great circle distance (km) between samples.
To test for differences in SES between ASD cases and the surveillance population, we computed t-tests for the indicators % poverty and % bachelors, and the two-sample median test for the indicator MHI.
To quantify the changes induced by the movement of the protrusion on the population level, we computed the ensemble averages for several types of correlations between the firing rates on the two protruding regions before and after the protrusion flip.
Three measures of divergence, FST (using ANGSD) and df, the number of fixed differences between populations were computed using custom scripts.
Pairwise FST between populations was computed as for the PUUV populations.
Genetic distances between populations were computed as Dest and specified as the predictor variable.
Next, a matrix of pairwise geographic distances between populations was computed from geographic coordinates and the correlation between genetic and geographic matrices was estimated using 999 permutations in GenAlEx.
Differentiation between populations was computed in ARLEQUIN using RST[ 50], which assumes a stepwise mutation model (SMM; [ 51]), and thus may be more realistic for microsatellite data than other measures (e.g., FST) based on the infinite alleles model (IAM).
To minimize bias in the estimation of pairwise relatedness between nestlings, we computed those values based on population allele frequencies estimated using independent population samples for each location (as described in the preceding section).
