Data from: 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.近年来，扩增片段长度多态性（Amplified Fragment Length Polymorphism，AFLP）片段自动化评分流程的应用日益增多。相关软件不仅可自动完成AFLP片段有无的评分，还能评估不同评分参数设置对后续群体遗传分析的影响。本研究借助自动化评分软件包RAWGENO，探究5个评分参数对多态性片段箱数量以及群体间两两遗传分化系数（Fixation Index，Fst）估计值的影响。本研究通过R语言编写脚本，针对一系列不同的参数组合，自动运行RAWGENO的评分流程。研究发现，最小片段箱宽度和每个片段箱的最小样本数这两个评分参数，对两两Fst值的影响较弱；而最大片段箱宽度与片段箱重现性的影响则显著更强。最小平均片段箱荧光评分参数对Fst值的影响仅为中等程度。当评分参数处于RAWGENO默认设置附近的区间时，多态性片段箱的数量与两两Fst值均保持相对稳定。综上，本研究表明，无论是手动还是自动化的AFLP评分流程，其自身的特殊性都会对后续的群体遗传分析产生深远影响。