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Comparing Facial 3D Analysis With DNA Testing to Determine Zygosities of Twins
- Source :
- Twin Research and Human Genetics. 18:306-313
- Publication Year :
- 2015
- Publisher :
- Cambridge University Press (CUP), 2015.
-
Abstract
- The aim of this study was to compare facial 3D analysis to DNA testing in twin zygosity determinations. Facial 3D images of 106 pairs of young adult Lithuanian twins were taken with a stereophotogrammetric device (3dMD, Atlanta, Georgia) and zygosity was determined according to similarity of facial form. Statistical pattern recognition methodology was used for classification. The results showed that in 75% to 90% of the cases, zygosity determinations were similar to DNA-based results. There were 81 different classification scenarios, including 3 groups, 3 features, 3 different scaling methods, and 3 threshold levels. It appeared that coincidence with 0.5 mm tolerance is the most suitable feature for classification. Also, leaving out scaling improves results in most cases. Scaling was expected to equalize the magnitude of differences and therefore lead to better recognition performance. Still, better classification features and a more effective scaling method or classification in different facial areas could further improve the results. In most of the cases, male pair zygosity recognition was at a higher level compared with females. Erroneously classified twin pairs appear to be obvious outliers in the sample. In particular, faces of young dizygotic (DZ) twins may be so similar that it is very hard to define a feature that would help classify the pair as DZ. Correspondingly, monozygotic (MZ) twins may have faces with quite different shapes. Such anomalous twin pairs are interesting exceptions, but they form a considerable portion in both zygosity groups.
- Subjects :
- Adult
Genetic Markers
Male
Similarity (geometry)
Genotype
Genotyping Techniques
Cephalometry
3d analysis
Sample (material)
Dna testing
Sensitivity and Specificity
Cohort Studies
Young Adult
Imaging, Three-Dimensional
Sex Factors
Double-Blind Method
Twins, Dizygotic
Feature (machine learning)
Humans
Genetics (clinical)
Mathematics
Genetics
business.industry
Age Factors
Reproducibility of Results
Obstetrics and Gynecology
Lithuania
Pattern recognition
DNA
Twins, Monozygotic
Twin study
Zygosity
Face
Pediatrics, Perinatology and Child Health
Outlier
Female
Artificial intelligence
Anatomic Landmarks
business
Subjects
Details
- ISSN :
- 18392628 and 18324274
- Volume :
- 18
- Database :
- OpenAIRE
- Journal :
- Twin Research and Human Genetics
- Accession number :
- edsair.doi.dedup.....ec29b667c60eedba38399075ae1399bc
- Full Text :
- https://doi.org/10.1017/thg.2015.16