Francesca Luca

The paper investigates how lifestyle-associated microbiome shifts and host genetics influence gene expression in intestinal organoids, identifying microbiome-dependent allele-specific expression effects.

fastdemux improves computational efficiency for SNP-based demultiplexing while maintaining accuracy in single-cell genomics data.

The paper identifies gene-microbe interactions that modulate host gene expression in the human intestine and links them to IBD risk.

The paper investigates host-microbiome metabolic interactions in colorectal cancer using computational and experimental methods, revealing how tumor metabolic changes support pathogenic microbes.

The paper compares host transcriptional responses to urban and rural gut microbiomes, finding urban microbiomes affect innate immune pathways and high-diversity microbiomes trigger stronger host responses.

The paper identifies opposing gene regulatory mechanisms in CD4+ T cells and monocytes associated with psychological stress and social support in African American adults using scRNA-seq and scATAC-seq.

The paper uses scATAC-seq to analyze chromatin accessibility and gene expression dynamics in immune cells from asthmatic children, identifying eQTLs and their regulatory roles in asthma risk.

This paper introduces INTERFACE, a probabilistic fine-mapping method that improves the identification of causal genes by integrating colocalization and transcriptome-wide association evidence.

The paper introduces Multi-INTACT, a method that integrates transcriptome-wide association studies with protein QTL data to identify causal genes for metabolites, finding that both gene products are relevant for most gene nominations.

The paper identifies genetic variants that modify gene expression in response to caffeine in vascular endothelial cells and shows their potential role in cardiovascular disease.

The paper uses single-cell RNA-seq to study how genetic variants influence the transcriptional response to glucocorticoids and immune stimuli in children, identifying treatment-specific gene regulation.

The paper analyzes single nucleus transcriptomics data from opioid overdose cases and controls to show widespread glial activation and changes in gene expression related to substance use traits.

The paper identifies gene expression changes in immune cells during pubertal development in children with asthma, showing shifts in immunity and correlations with asthma-related gene expression.

The paper identifies 138 genes differentially expressed in blood immune cells associated with poverty, enriched in wound healing and coagulation, and linked to hypertension.

The paper identifies environmental and genetic factors influencing population differences in SARS-CoV-2 immune responses using single-cell RNA-sequencing data.

This paper introduces a probabilistic framework to integrate TWAS and colocalization analysis, improving gene implication and pathway identification for complex traits.

This paper investigates the inferential reproducibility between transcriptome-wide association studies and colocalization analysis, identifying two classes of inconsistent results and proposing a novel approach to reconcile them.

The paper investigates how interspecies variation in hominid gut microbiota affects host gene regulation in colonic epithelial cells, finding species-specific gene responses linked to inflammatory diseases.

The paper identifies 174 asthma-associated genes regulated by psychosocial factors and 349 gene-environment interactions using RNA-sequencing and machine learning in children with asthma.

The paper identifies gene-environment interactions in gene regulation across cell types and treatments, revealing many genes missed by GTEx.

The paper evaluates colocalization methods for genetic variants, identifying limitations and recommending best practices for accurate analysis of complex traits and molecular QTLs.

The paper investigates ACE2 and TMPRSS2 expression in human placenta across pregnancy stages and finds negligible co-expression, suggesting SARS-CoV-2 is unlikely to infect placenta via canonical entry mediators.

The paper analyzes the viral-host interactome of SARS-CoV, MERS-CoV, and HCoV-229E using a network-based approach to predict SARS-CoV-2 pathogenesis.

The paper uses scRNA-seq to analyze placental tissues from term and preterm births, identifying cell type differences and transcriptional signatures associated with labor.

BAGSE provides a Bayesian hierarchical model for gene set enrichment analysis, offering accurate enrichment quantification and improved power in gene discovery.

This paper introduces PTWAS, a probabilistic TWAS framework that detects gene expression-trait associations and estimates tissue-specific causal effects using eQTL data and GWAS summary statistics.

The paper investigates gene-environment interactions in coronary artery disease by analyzing RNA-seq and ATAC-seq data from endothelial cells exposed to environmental factors, finding links between environmental responses and CAD risk.

The paper shows gut microbiota influences host gene regulation, identifying specific taxa and genes, and demonstrates microbiome manipulation can alter gene expression profiles.

The paper develops a high-throughput assay to identify allele-specific effects on DNA:protein binding and gene transcription, finding significant associations with complex trait variants.

circuitSNPs predicts the functional effects of genetic variants on chromatin accessibility using a neural network that models regulatory modules from DNase-seq footprints.