UMR AGAP, INRA, Bât 33, 2 place Viala, 34060 Montpellier Cedex 1, France.
Mol Ecol Resour. 2011 Jul;11(4):733-8. doi: 10.1111/j.1755-0998.2011.02993.x. Epub 2011 Feb 28.
AMaCAID is an R program designed to analyse multilocus genotypic patterns in large samples. It allows (i) the computation of the number and frequency of the different multilocus patterns available in a molecular data set and (ii) the analysis of discriminatory power of each combination of k markers among n available. It thus enables the identification of the minimum number of markers required to distinguish all the observed genotypes and the subset of markers that maximize the number of distinct genotypes. AMaCAID can be used with any kind of molecular markers, on data sets mixing different kinds of markers, but also on qualitative characters like morphological or taxonomic traits. AMaCAID has been built primarily to select subsets of markers for identifying accessions and monitoring their genetic stability during regeneration cycles in an ex situ genebank. It can, however, also be used to screen any kind of data set that characterizes a set of individuals or species (e.g. taxonomic or phylogenetic studies) for discrimination purposes. The size of the assayed sample has no limitation, but the program only performs computations on all combinations of markers when there are less than 25 markers. For larger number of markers/characters, it is possible to ask AMaCAID to screen a large but limited number of combinations of markers. We apply AMaCAID to three data sets involving either molecular or taxonomic data and give some results on the computing time of the program with respect to the size of the data set.
AMaCAID 是一个 R 程序,用于分析大量样本中的多位点基因型模式。它允许:(i)计算分子数据集内可用的不同多位点模式的数量和频率;(ii)分析 n 个标记中每 k 个标记组合的区分能力。因此,它可以确定区分所有观察到的基因型所需的最小标记数量,以及最大限度增加不同基因型数量的标记子集。AMaCAID 可用于任何类型的分子标记,也可用于混合不同类型标记的数据集中,还可用于定性特征,如形态或分类特征。AMaCAID 主要用于选择标记子集,以识别个体并监测其在原地基因库再生循环中的遗传稳定性。然而,它也可用于筛选任何用于区分目的的数据集,例如描述一组个体或物种的数据集(例如分类或系统发育研究)。被检测样本的大小没有限制,但程序仅在标记数少于 25 时才对所有标记组合进行计算。对于更多的标记/特征,可以要求 AMaCAID 筛选大量但有限数量的标记组合。我们将 AMaCAID 应用于三个涉及分子或分类数据的数据集,并给出了程序在处理数据集大小时的计算时间的一些结果。