Browsing by Author "Walsh, Susan"
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Item 3D Facial Matching by Spiral Convolutional Metric Learning and a Biometric Fusion-Net of Demographic Properties(IEEE, 2021) Mahdi, Soha Sadat; Nauwelaers, Nele; Joris, Philip; Bouritsas, Giorgos; Gong, Shunwang; Bokhnyak, Sergiy; Walsh, Susan; Shriver, Mark D.; Bronstein, Michael; Claes, Peter; Biology, School of ScienceFace recognition is a widely accepted biometric verification tool, as the face contains a lot of information about the identity of a person. In this study, a 2-step neural-based pipeline is presented for matching 3D facial shape to multiple DNA-related properties (sex, age, BMI and genomic background). The first step consists of a triplet loss-based metric learner that compresses facial shape into a lower dimensional embedding while preserving information about the property of interest. Most studies in the field of metric learning have only focused on 2D Euclidean data. In this work, geometric deep learning is employed to learn directly from 3D facial meshes. To this end, spiral convolutions are used along with a novel mesh-sampling scheme that retains uniformly sampled 3D points at different levels of resolution. The second step is a multi-biometric fusion by a fully connected neural network. The network takes an ensemble of embeddings and property labels as input and returns genuine and imposter scores. Since embeddings are accepted as an input, there is no need to train classifiers for the different properties and available data can be used more efficiently. Results obtained by a to-fold cross-validation for biometric verification show that combining multiple properties leads to stronger biometric systems. Furthermore, the proposed neural-based pipeline outperforms a linear baseline, which consists of principal component analysis, followed by classification with linear support vector machines and a Naïve Bayes-based score-fuser.Item 3D facial phenotyping by biometric sibling matching used in contemporary genomic methodologies(Public Library of Science, 2021-05-13) Hoskens, Hanne; Liu, Dongjing; Naqvi, Sahin; Lee, Myoung Keun; Eller, Ryan J.; Indencleef, Karlijne; White, Julie D.; Li, Jiarui; Larmuseau, Maarten H. D.; Hens, Greet; Wysocka, Joanna; Walsh, Susan; Richmond, Stephen; Shriver, Mark D.; Shaffer, John R.; Peeters, Hilde; Weinberg, Seth M.; Claes, Peter; Biology, School of ScienceThe analysis of contemporary genomic data typically operates on one-dimensional phenotypic measurements (e.g. standing height). Here we report on a data-driven, family-informed strategy to facial phenotyping that searches for biologically relevant traits and reduces multivariate 3D facial shape variability into amendable univariate measurements, while preserving its structurally complex nature. We performed a biometric identification of siblings in a sample of 424 children, defining 1,048 sib-shared facial traits. Subsequent quantification and analyses in an independent European cohort (n = 8,246) demonstrated significant heritability for a subset of traits (0.17-0.53) and highlighted 218 genome-wide significant loci (38 also study-wide) associated with facial variation shared by siblings. These loci showed preferential enrichment for active chromatin marks in cranial neural crest cells and embryonic craniofacial tissues and several regions harbor putative craniofacial genes, thereby enhancing our knowledge on the genetic architecture of normal-range facial variation.Item Advancements in forensic DNA-based identification(2017) Dembinski, Gina M.; Picard, Christine; Christie, Mark; Walsh, Susan; Randall, Stephen; Goodpaster, JohnModern DNA profiling techniques have increased in sensitivity allowing for higher success in producing a DNA profile from limited evidence sources. However, this can lead to the amplification of more DNA profiles that do not get a hit on a suspect or DNA database and more mixture profiles. The work here aims to address or improve these consequences of current DNA profiling techniques. Based on allele-specific PCR and quantitative color measurements, a 24-SNP forensic phenotypic profile (FPP) assay was designed to simultaneously predict eye color, hair color, skin color, and ancestry, with the potential for age marker incorporation. Bayesian Networks (BNs) were built for model predictions based on a U.S sample population of 200 individuals. For discrete pigmentation traits using an ancestry influenced pigmentation prediction model, AUC values were greater than 0.65 for the eye, hair, and skin color categories considered. For ancestry using an all SNPs prediction model, AUC values were greater than 0.88 for the 5 continental ancestry categories considered. Quantitative pigmentation models were also built with prediction output as RGB values; the average amount of error was approximately 7% for eye color, 12% for hair color, and 8% for skin color. A novel sequencing method, methyl-RADseq, was developed to aid in the discovery of candidate age-informative CpG sites to incorporate into the FPP assay. There were 491 candidate CpG sites found that either increased or decreased with age in three forensically relevant xii fluids with greater than 70% correlation: blood, semen, and saliva. The effects of exogenous microbial DNA on human DNA profiles were analyzed by spiking human DNA with differing amounts of microbial DNA using the Promega PowerPlex® 16 HS kit. Although there were no significant effects to human DNA quantitation, two microbial species, B. subtilis and M. smegmatis, amplified an allelic artifact that mimics a true allele (‘5’) at the TPOX locus in all samples tested, interfering with the interpretation of the human profile. Lastly, the number of contributors of theoretically generated 2-, 3-, 4-, 5-, and 6-person mixtures were evaluated via allele counting with the Promega PowerPlex® Fusion 6C system, an amplification kit with the newly expanded core STR loci. Maximum allele count in the number of contributors for 2- and 3-person mixtures was correct in 99.99% of mixtures. It was less accurate in the 4-, 5-, and 6-person mixtures at approximately 90%, 57%, and 8%, respectively. This work provides guidance in addressing some of the limitations of current DNA technologies.Item Advancing Genotype-Phenotype Analysis through 3D Facial Morphometry: Insights from Cri-du-Chat Syndrome(medRxiv, 2025-06-01) Vanneste, Michiel; Matthews, Harold; Sleyp, Yoeri; Hammond, Peter; Shriver, Mark; Weinberg, Seth M.; Marazita, Mary L.; Walsh, Susan; Hallgrímsson, Benedikt; Klein, Ophir D.; Spritz, Richard A.; Van Den Bogaert, Kris; Claes, Peter; Peeters, Hilde; Biology, School of SciencePurpose: Facial dysmorphism is a feature of many monogenic disorders, and is important in diagnostics, variant interpretation and nosology. Nevertheless, comprehensively assessing the complex facial shape changes associated with specific syndromes remains challenging. Here, we present 3D morphometric approaches to overcome these limitations, utilizing Cri-du-Chat syndrome (CdCS) as a model. Methods: We analyzed 3D facial photos from 24 individuals with CdCS, 4540 unaffected controls and 5 individuals with rare 5p15.33-15.32 deletions, incorporating two methods to account for age- and sex-related facial variation. We quantified phenotypic variation within and between groups and explored genotype-phenotype correlations in CdCS. Results: We identified changes in the characteristic facial features of CdCS with age and found that facial shape in CdCS differed from controls in highly consistent directions, but with varying magnitudes of effect. 5p15.33-15.32 heterozygotes had non-specific dysmorphic features that were objectively different from those in CdCS, delineating multiple critical regions for facial dysmorphism on chromosome 5p. Conclusion: This work explores 3D facial morphometry to complement the standard clinical assessment of facial dysmorphism. It provides insights into the genetic basis of facial shape in CdCS and highlights the potential of 3D morphometric techniques to facilitate clinical diagnostics, variant interpretation, and delineation of syndrome nosology.Item Ancient genomes indicate population replacement in Early Neolithic Britain(Springer Nature, 2019-05) Brace, Selina; Diekmann, Yoan; Booth, Thomas J.; van Dorp, Lucy; Faltyskova, Zuzana; Rohland, Nadin; Mallick, Swapan; Olalde, Iñigo; Ferry, Matthew; Michel, Megan; Oppenheimer, Jonas; Broomandkhoshbacht, Nasreen; Stewardson, Kristin; Martiniano, Rui; Walsh, Susan; Kayser, Manfred; Charlton, Sophy; Hellenthal, Garrett; Armit, Ian; Schulting, Rick; Craig, Oliver E.; Sheridan, Alison; Parker Pearson, Mike; Stringer, Chris; Reich, David; Thomas, Mark G.; Barnes, Ian; Biology, School of ScienceThe roles of migration, admixture and acculturation in the European transition to farming have been debated for over 100 years. Genome-wide ancient DNA studies indicate predominantly Aegean ancestry for continental Neolithic farmers, but also variable admixture with local Mesolithic hunter-gatherers. Neolithic cultures first appear in Britain circa 4000 BC, a millennium after they appeared in adjacent areas of continental Europe. The pattern and process of this delayed British Neolithic transition remain unclear. We assembled genome-wide data from 6 Mesolithic and 67 Neolithic individuals found in Britain, dating 8500-2500 BC. Our analyses reveal persistent genetic affinities between Mesolithic British and Western European hunter-gatherers. We find overwhelming support for agriculture being introduced to Britain by incoming continental farmers, with small, geographically structured levels of hunter-gatherer ancestry. Unlike other European Neolithic populations, we detect no resurgence of hunter-gatherer ancestry at any time during the Neolithic in Britain. Genetic affinities with Iberian Neolithic individuals indicate that British Neolithic people were mostly descended from Aegean farmers who followed the Mediterranean route of dispersal. We also infer considerable variation in pigmentation levels in Europe by circa 6000 BC.Item Automated 3D Landmarking of the Skull: A Novel Approach for Craniofacial Analysis(bioRxiv, 2024-02-12) Wilke, Franziska; Matthews, Harold; Herrick, Noah; Dopkins, Nichole; Claes, Peter; Walsh, Susan; Biology, School of ScienceAutomatic dense 3D surface registration is a powerful technique for comprehensive 3D shape analysis that has found a successful application in human craniofacial morphology research, particularly within the mandibular and cranial vault regions. However, a notable gap exists when exploring the frontal aspect of the human skull, largely due to the intricate and unique nature of its cranial anatomy. To better examine this region, this study introduces a simplified single-surface craniofacial bone mask comprising 9,999 quasi-landmarks, which can aid in the classification and quantification of variation over human facial bone surfaces. Automatic craniofacial bone phenotyping was conducted on a dataset of 31 skull scans obtained through cone-beam computed tomography (CBCT) imaging. The MeshMonk framework facilitated the non-rigid alignment of the constructed craniofacial bone mask with each individual target mesh. To gauge the accuracy and reliability of this automated process, 20 anatomical facial landmarks were manually placed three times by three independent observers on the same set of images. Intra- and inter-observer error assessments were performed using root mean square (RMS) distances, revealing consistently low scores. Subsequently, the corresponding automatic landmarks were computed and juxtaposed with the manually placed landmarks. The average Euclidean distance between these two landmark sets was 1.5mm, while centroid sizes exhibited noteworthy similarity. Intraclass coefficients (ICC) demonstrated a high level of concordance (>0.988), and automatic landmarking showing significantly lower errors and variation. These results underscore the utility of this newly developed single-surface craniofacial bone mask, in conjunction with the MeshMonk framework, as a highly accurate and reliable method for automated phenotyping of the facial region of human skulls from CBCT and CT imagery. This craniofacial template bone mask expansion of the MeshMonk toolbox not only enhances our capacity to study craniofacial bone variation but also holds significant potential for shedding light on the genetic, developmental, and evolutionary underpinnings of the overall human craniofacial structure.Item Automatic Landmark Placement for Large 3D Facial Image Dataset(IEEE, 2019-12) Wang, Jerry; Fang, Shiaofen; Fang, Meie; Wilson, Jeremy; Herrick, Noah; Walsh, Susan; Computer and Information Science, School of ScienceFacial landmark placement is a key step in many biomedical and biometrics applications. This paper presents a computational method that efficiently performs automatic 3D facial landmark placement based on training images containing manually placed anthropological facial landmarks. After 3D face registration by an iterative closest point (ICP) technique, a visual analytics approach is taken to generate local geometric patterns for individual landmark points. These individualized local geometric patterns are derived interactively by a user's initial visual pattern detection. They are used to guide the refinement process for landmark points projected from a template face to achieve accurate landmark placement. Compared to traditional methods, this technique is simple, robust, and does not require a large number of training samples (e.g. in machine learning based methods) or complex 3D image analysis procedures. This technique and the associated software tool are being used in a 3D biometrics project that aims to identify links between human facial phenotypes and their genetic association.Item Characterization of Simple Sequence Repeats in Phormia Regina Miegen (Diptera: Callphoridae)(2024-08) Waletzko, Cassandra; Picard, Christine; Walsh, Susan; Owings, CharityPhormia regina Meigen is a forensically relevant species of blow fly, common in North America and used to estimate the minimum postmortem interval in forensic casework. It is also possible to use blow flies to survey the environment for biotic and abiotic information drawn from both larval and adult stages. There are both forensic and environmental uses for genetic analysis of blow flies. Blow fly kinship is especially useful for detecting postmortem movement of a corpse or to assess abundance of carrion in a given location. To test genetic relationships between individuals, discriminatory loci such as microsatellites, or polymorphic tandemly repeated sequences of DNA are necessary. Here, we characterize novel microsatellites generated from the genome of P. regina. Thirty-four candidate polymorphic loci with conserved flanking regions, have been isolated. To date, seven are heterozygous and polymorphic testing in two lab populations and one wild population. The simple sequence repeats characterized here complement existing loci (N = 6) for greater discrimination for testing relationships between individual flies.Item Clustering individuals using INMTD: a novel versatile multi-view embedding framework integrating omics and imaging data(Oxford University Press, 2025) Li, Zuqi; Windels, Sam F. L.; Malod-Dognin, Noël; Weinberg, Seth M.; Marazita, Mary L.; Walsh, Susan; Shriver, Mark D.; Fardo, David W.; Claes, Peter; Pržulj, Nataša; Van Steen, Kristel; Biology, School of ScienceMotivation: Combining omics and images can lead to a more comprehensive clustering of individuals than classic single-view approaches. Among the various approaches for multi-view clustering, nonnegative matrix tri-factorization (NMTF) and nonnegative Tucker decomposition (NTD) are advantageous in learning low-rank embeddings with promising interpretability. Besides, there is a need to handle unwanted drivers of clusterings (i.e. confounders). Results: In this work, we introduce a novel multi-view clustering method based on NMTF and NTD, named INMTD, which integrates omics and 3D imaging data to derive unconfounded subgroups of individuals. According to the adjusted Rand index, INMTD outperformed other clustering methods on a synthetic dataset with known clusters. In the application to real-life facial-genomic data, INMTD generated biologically relevant embeddings for individuals, genetics, and facial morphology. By removing confounded embedding vectors, we derived an unconfounded clustering with better internal and external quality; the genetic and facial annotations of each derived subgroup highlighted distinctive characteristics. In conclusion, INMTD can effectively integrate omics data and 3D images for unconfounded clustering with biologically meaningful interpretation. Availability and implementation: INMTD is freely available at https://github.com/ZuqiLi/INMTD.Item Covariate and Co-Structural Influences on Human Facial Morphology: Decoding the Structural Blueprint Behind Facial Shape(2025-05) Wilke, Franziska; Walsh, Susan; Roper, Randall; Balakrishnan, Lata; Wilson, Jeremy; Wetherill, Leah; Lapish, ChristopherThe human face is one of the most intricate yet informative structures, serving as a key identifier in forensic investigations, an indicator of medical conditions, and a crucial factor in surgical planning. Over the past few decades, significant effort has been dedicated to understanding the genetic architecture underlying facial morphology. However, this focus often overlooks the substantial influence of covariates, such as biogeographic ancestry, and structural components like the skull. While these factors are acknowledged, their anthropological is frequently reduced to statistical models that bypass anatomical considerations. Furthermore, many of the complex models developed to reconstruct facial shape are not yet practically applicable. This dissertation addresses these gaps by investigating how regional, rather than just global, biogeographic ancestry influences facial morphology and whether genetic models of biogeographic ancestry align with phenotypic expression. Our findings indicate that broad categorizations such as “European” do not fully capture ancestral variation, yet incorporating too many genetic principal components risks overcorrection. To address this, we introduce a novel standardized, phenotype-based approach using consensus faces. Additionally, we present a validated, standardized method for efficiently masking and analyzing the human skull using over 6,000 quasi-landmarks. This methodology is further expanded to include a facial mask, where both the skull and face are intrinsically linked through anatomically corresponding quasi-landmarks. This innovation enables the simultaneous study of facial soft tissue thickness (FSTT), cranial shape, and facial morphology in a computationally efficient manner that has not been previously achieved. The use of correspondence masks permits modeling of the relationship between the skull and face, facilitating craniofacial reconstruction and laying the foundation for an open-source FSTT and facial measurement database. Ultimately, this dissertation explores standardization, global applicability, with the aim of facilitating real-world applications of a scientifically transparent computational approach to facial image projection from skeletal remains. By integrating genetic, anthropological, and statistical approaches, it describes a streamlined methodology that can harness structural knowledge of facial variation to develop practical tools useful in forensic and medical applications. Moreover, it highlights the need for global large-scale collaborative research to further advance this field on both fundamental science and applied levels.