Influence of parameter settings in automated scoring of AFLPs on population genetic analysis

The use of procedures for the automated scoring of AFLP fragments has recently increased. Corresponding software does not only automatically score the presence or absence of AFLP fragments, but also allows an evaluation of how different settings of scoring parameters influence subsequent population genetic analyses. In this study, we used the automated scoring package RAWGENO to evaluate how five scoring parameters influence the number of polymorphic bins and estimates of pairwise genetic differentiation between populations (Fst). Steps were implemented in R to automatically run the scoring process in RAWGENO for a set of different parameter combinations. While we found the scoring parameters minimum bin width and minimum number of samples per bin to have only weak influence on pairwise Fst values, maximum bin width and bin reproducibility had much stronger effects. The minimum average bin fluorescence scoring parameter affected Fst values in an only moderate way. At a range of scoring parameters around the default settings of RAWGENO, the number of polymorphic bins as well as pairwise Fst values stayed rather constant. This study thus shows the particularities of AFLP scoring, be it either manual or automatical, can have profound effects on subsequent population genetic analysis.