Jacometti Victor, Guimarães Marco Aurelio, de Moraes Luis Otávio Carvalho, Marques Sérgio Ricardo, Cunha Eugénia, da Silva Ricardo Henrique Alves
Department of Pathology and Legal Medicine, Ribeirão Preto Medical School, University of São Paulo, 14048-900 Ribeirão Preto, Brazil.
Discipline of Descriptive and Topografic Anatomy, Department of Morphology and Genetics, Federal University of São Paulo, 04024-002 São Paulo, Brazil.
Forensic Sci Res. 2023 Nov 10;8(3):202-210. doi: 10.1093/fsr/owad030. eCollection 2023 Sep.
The objective of this study is to analyze the accuracy and applicability of the AncesTrees software with respect to a set of cranial measurements of a Brazilian sample consisting of 114 identified skulls from two osteological collections, predominantly composed of European ( = 59), African ( = 35), and admixed individuals ( = 20). Twenty-four different craniometric measurements are performed and input to AncesTrees two algorithms, one of which is used in three configurations, with different ancestral groups integrated in the model. The software exhibits superior performance in the estimation of European individuals, reaching 73% accuracy, compared with 66% in the African individuals. Those individuals classified as admixed produce a variety of ancestral classifications, mainly European. Overall, the most accurate combination of AncesTrees is obtained using ancestralForest with only the European and African groups integrated into the algorithm, where the accuracy reaches 70%. The applicability of this software to a specific population is fragile because of the high admixing load, making it necessary to create a more representative anthropometric database of the Brazilian people.
Ancestry estimation methods are seldom validated in Brazil.AncesTrees performed poorly on our sample, with a maximum accuracy of 70%.Brazil's highly mixed population hinders ancestry estimation.Mixed individuals (pardos) are predominantly classified as Europeans.The insertion of Brazilian metric data into the AncesTrees database would produce better results.
本研究的目的是分析AncesTrees软件在一组巴西样本颅骨测量方面的准确性和适用性,该样本由来自两个骨学收藏的114个已识别颅骨组成,主要包括欧洲人(=59)、非洲人(=35)和混血个体(=20)。进行了24种不同的颅骨测量,并将其输入到AncesTrees的两种算法中,其中一种算法以三种配置使用,模型中整合了不同的祖先群体。该软件在估计欧洲个体时表现出卓越性能,准确率达到73%,而非洲个体的准确率为66%。那些被归类为混血的个体产生了多种祖先分类,主要是欧洲人。总体而言,AncesTrees最准确的组合是使用仅将欧洲和非洲群体整合到算法中的ancestralForest获得的,准确率达到70%。由于高度的混血比例,该软件在特定人群中的适用性很脆弱,因此有必要创建一个更具代表性的巴西人群体人体测量数据库。
血统估计方法在巴西很少得到验证。AncesTrees在我们的样本上表现不佳,最高准确率为70%。巴西高度混血的人口阻碍了血统估计。混血个体(pardos)主要被归类为欧洲人。将巴西的测量数据插入AncesTrees数据库会产生更好的结果。