Gillian M. Belbin

SPC improves population structure adjustment in genomic analysis by capturing fine-scale patterns better than principal components, reducing p-value inflation and improving rare variant associations.

The paper imputes structural variants using a multi-ancestry long-read sequencing panel and identifies disease associations in large-scale datasets.

This study evaluates how perturbations in haplotype reference panels affect genotype imputation accuracy, finding that phase and genotype errors have a greater impact than variant density.

The paper identifies a novel risk locus for PAD on 2q35 in Dominicans using admixture mapping and health systems data.

The paper selects and validates ten polygenic risk scores for clinical use in diverse populations, focusing on chronic diseases and addressing disparities in predictive performance.

The paper quantifies similarity in causal effects across local ancestries in admixed individuals and finds high genetic correlation (radmix=0.95) within individuals.

The paper analyzes genomic data from the Chabu, a hunter-gatherer group in Ethiopia, revealing a population bottleneck and diverse demographic responses to agropastoralism in East Africa.

The paper identifies a risk variant for liver disease in Puerto Ricans by integrating EHR and genomic data, showing a dose-dependent association with disease severity.

This study evaluates the prognostic value of polygenic risk scores for schizophrenia and finds they do not improve outcome prediction beyond clinical features.

The paper evaluates clustering algorithms for IBD mapping, finding that Markov Clustering outperforms others in statistical power and efficiency.

The paper introduces iLASH, an algorithm for fast and accurate detection of identity-by-descent tracts in large genomic datasets, achieving significant speed improvements over existing methods.

This study links genomic data with EHRs to identify health outcomes enriched in sub-populations, revealing both known and novel associations.

This paper reports on a pilot genomic screening program in a diverse population, finding higher return rates for hATTR results in African/African American and Hispanic/Latinx participants.

This study identifies genetic factors influencing blood pressure response to phenylephrine in perioperative settings, revealing population-specific differences and rare variants associated with non-response.

The paper uses exome sequencing and EHR data to find BRCA1/2 pathogenic variants in a diverse biobank population, revealing high prevalence in certain ancestry groups and gaps in knowledge for non-European populations.

A common missense variant in FBN1 reduces height by 2.2 cm in Peruvians, showing strong positive selection and higher frequency in coastal Native American populations.

The paper identifies VGF as a key regulator of Alzheimer’s disease using multiscale causal network models and validates its protective role in mouse models.

The paper identifies a common collagen disease in Puerto Ricans using identity-by-descent mapping and genomic data from a health system.

The paper uses next-of-kin data from electronic health records to estimate heritability for 500 disease phenotypes, finding results consistent with existing literature.