Katherine S. Pollard

SuPreMo is a tool for in silico mutagenesis using sequence-based predictive models to prioritize pathogenic variants and discover functional sequences.

The paper identifies 46,802 enhancers and 164 psychiatric disorder variants with regulatory effects in the developing cortex and organoids using massively parallel reporter assays and deep learning.

CellWalker2 improves cell type annotation and mapping by integrating multi-omic data and hierarchical relationships, outperforming existing methods in simulations and demonstrating applications in brain and immune system data.

The paper introduces StrainPGC and MIDAS v3 to accurately estimate intraspecific microbial gene content variation in metagenomic data, outperforming existing methods and revealing functional diversity in gut microbiomes.

The paper identifies proteins and regulatory elements associated with vocal learning by analyzing bat neural activity and epigenomic data.

This study presents contiguous and complete assemblies of Blastocystis strains, revealing genetic and metabolic diversity linked to host ecology and horizontal gene transfer.

The paper develops a hierarchical model to annotate bulk eQTLs with cell-type specificity using single-cell chromatin data, identifying genes with divergent regulation across cell types.

The paper uses deep learning to assess how sequence changes affect chromatin organization, finding that repetitive elements and noncoding RNA genes significantly influence 3D genome structure.

Maast efficiently genotypes SNPs from thousands of microbial strains by reducing redundancy and improving speed and accuracy compared to existing methods.

TOGA integrates gene annotation and orthology inference across hundreds of genomes, improving ortholog detection and creating large comparative gene resources.

A machine learning approach identifies enhancer-phenotype associations across mammals, revealing links to brain size and behavior evolution.

The paper curates TE content in 248 mammalian genomes, finding trends in recent TE accumulation and associations with dietary habits.

A 240-species placental mammal alignment resolves constraint to single bases, estimating at least 10.7% of the human genome is constrained, with 48.5% of constrained bases unannotated.

The paper uses evolutionary constraint scores to identify functional genomic regions and finds they are enriched for variants associated with common diseases.

The paper identifies bats as a hotspot for horizontal transfer of DNA transposons, finding over 200 putative elements and shared transposons across mammals and reptiles.

The paper constructs a cross-ancestry, cell-type-informed gene regulatory atlas of the developing human brain, identifying genetic regulation and linking it to neuropsychiatric disorders.

The paper maps lamin-associated chromatin across twelve human cell types, identifying two subtypes with distinct features and developmental dynamics.

The paper shows that closely related microbial species in genome databases reduce metagenotyping accuracy and power, and suggests strategies to mitigate these issues.

The paper identifies BRD4-dependent immune-fibroblast crosstalk via IL1B in heart failure, showing IL1B inhibition reduces fibroblast activation and improves cardiac function.

MIDAS2 improves metagenomic analysis by enhancing SNV and CNV detection with custom databases and paired-end reads, enabling efficient genotyping of large sample sets.

The paper uses single-cell epigenomics and machine learning to model cell-cell communication networks in cardiac development and identify dysregulation in TBX1 deletion.

StrainFacts enables scalable strain inference in metagenomic data, showing comparable accuracy to intensive tools and revealing strain diversity patterns in human stool samples.

The paper introduces a method to detect gene combinations contributing to congenital heart defects and their comorbidities by analyzing exome sequencing data from families.

CellWalkR integrates scATAC-seq with bulk epigenetic data to improve identification of cell type-specific regulatory regions by using a network-based random walk model.

This study uses single-cell RNA-sequencing to analyze cell type-specific responses to young or aged blood in heterochronic parabiosis, identifying mitochondrial function as a key factor in rejuvenation.

Cell Layers provides an interactive tool to explore single-cell clustering across resolutions, linking molecular data with cluster evaluation metrics.

This paper introduces GT-Pro, a tool for ultra-fast and accurate SNP calling in metagenomes, enabling strain-level analysis of the human gut microbiome.

The paper shows POGZ promotes chromatin accessibility and expression of synaptic genes in mouse and human brains, and its reduction disrupts cortical function through interactions with ADNP.

The paper investigates how meiotic chromatin organization influences recombination activity by analyzing 3D chromosomal structure and recombination rates at PRDM9 hotspots.