Karin S. Dorman

CLEAR improves gene set enrichment analysis by jointly modeling gene sets with continuous statistics, reducing redundancy and improving sensitivity.

PREMISE improves metagenomic source assignment by using a quality-aware probabilistic framework, achieving high accuracy in both species and strain-level classification.

The paper introduces MULTICLUST, a fast maximum likelihood method for clustering multiallelic genotypes to infer genetic population structure, showing comparable accuracy and efficiency to existing methods.

This paper identifies the NOD1-RIPK2-NFkB axis as a critical inflammatory pathway for hematopoietic stem cell specification from human pluripotent stem cells.

The paper develops an interpretable model to predict antimicrobial resistance in Escherichia coli from livestock and companion animals using genomic and phenotypic data.

The paper introduces an unsupervised contrastive learning method for ATAC-seq peak calling that outperforms existing methods using replicates and annotations.

DAUMI improves UMI-based abundance estimation by accounting for UMI collisions and errors, outperforming existing methods on simulated and real data.

CAPG improves genotyping of allopolyploids by explicitly weighting read alignments against subgenomic references, reducing false heterozygous calls in whole genome sequencing data.

Y2H-SCORES provides a statistical framework to identify protein-protein interactions from yeast-two-hybrid sequence data by evaluating enrichment, specificity, and in-frame selection.

AmpliCI improves denoising of Illumina amplicon data by using a model-based approach that incorporates quality information, outperforming existing methods.

MetaOmGraph enables interactive exploratory analysis of large expression datasets, identifying novel biomarker genes in cancer and plant metabolomics.

The paper introduces phylostratr, an R package for phylostratigraphy, enabling automated and customizable analysis of gene evolutionary origins across species.