Christa Caggiano

This paper introduces PGSC, a polygenic score framework that incorporates locus-specific gene-context interactions, showing improved prediction across multiple traits and ancestries.

This paper surveys early-career researchers on their understanding and implementation of ethical guidelines for population descriptors in genomics, highlighting misconceptions and structural barriers.

The paper analyzes genetic and health record data from a diverse population to uncover gene-phenotype associations and assess polygenic score performance across ancestries.

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 uses unmapped reads from whole-exome sequencing data in the UK BioBank to construct features and identify 21 novel genetic loci associated with immune-related traits.

The paper evaluates the impact of non-random mating and environmental transmission on genetic methods and introduces a simulation tool to improve robustness.

The paper identifies tissue-informative DNA methylation sites in ALS using targeted sequencing and machine learning, showing accurate prediction of disease status and progression.

This study uses bulk RNA-Seq from blood samples to estimate cell type proportions and eQTLs, revealing cell-type specific genetic associations with psychiatric disorders and medication effects.

The paper explores the relationship between genomic ancestry and health outcomes using a biobank linked to electronic health records, finding disease stratification across ancestry clusters.

This study evaluates how blood collection tubes and time delay affect cfDNA methylation, finding robust results across tubes but recommending EDTA tubes processed within 24 hours.

This paper introduces CelFiE, a method to estimate cell type contributions to cfDNA, showing it can detect rare cell types and find increased skeletal muscle cfDNA in ALS patients.