Mark D. Shriver

This study identifies fine-scale population structure within Madagascar using genome-wide data, revealing distinct subpopulations and historical migration patterns.

The paper uses 3D craniofacial data and genome-wide association analysis to link craniofacial variation to genetic diversity, evolutionary processes, and clinical conditions in modern humans.

This paper uses 3D facial morphometry to analyze facial shape changes in Cri-du-Chat syndrome and related genetic conditions, identifying genotype-phenotype correlations and critical genomic regions.

The paper analyzes how SNP heritability estimates are affected by admixture and directional LD, showing biases in random-effect estimators and implications for GWAS and polygenic prediction.

INMTD integrates omics and 3D imaging data to produce unconfounded individual subgroups with biologically meaningful embeddings.

This study compares univariate phenotyping strategies for 3D facial shape in GWAS, finding that inter-landmark distances and AE-derived dimensions show higher heritability than facial resemblance to gestalts.

The paper identifies genomic loci associated with achondroplasia-like facial variation in the general population using a syndrome-informed phenotyping approach.

netMUG identifies actionable subgroups using network-guided multi-view clustering, showing improved performance over existing methods in synthetic and real data.

This paper introduces a method to extract genetically relevant facial phenotypes by optimizing trait heritability, showing higher heritability and better GWAS performance compared to principal components.

This study performs a joint multi-ancestry and admixed GWAS on cranial vault shape, identifying 30 genome-wide significant loci and highlighting genetic pathways involved in craniofacial development.

This paper introduces a hybrid autoencoder method for robust population structure inference, improving accuracy in the presence of missing data and relatedness.

The paper introduces a high-throughput method for imaging and analyzing scalp hair morphology and validates a Python package for processing and measuring hair images.

This study identifies 203 genomic regions associated with facial variation using GWAS on multivariate shape phenotypes, revealing novel regions and epistatic interactions.

This study identifies shared genetic loci influencing brain and facial shape, distinct from cognitive traits, suggesting a developmental link between brain and face formation.

This paper introduces SUGIBS, a robust genome-wide ancestry inference method, and applies it to predict ancestry faces using the 1000 Genomes Project and facial imaging data.

The paper analyzes genomic data from Mesolithic Scandinavians to show two colonization routes and genetic adaptations to high-latitude environments.