Erin K. Molloy

InSTability identifies seed-sensitive clustering regions in spatial transcriptomics data, revealing instability patterns and their impact on downstream analyses.

The paper investigates whether reconstructing level-1 blobs in phylogenetic networks is easy once the tree of blobs is known, presenting a fast algorithm that achieves comparable accuracy to existing methods.

The paper introduces TOB-QMC, a method for scalable and accurate tree of blobs reconstruction under network multispecies coalescent, improving upon TINNiK in both speed and accuracy.

The paper defines a new correct tagging criterion for gene trees under the DLCoal model and evaluates ASTRAL-pro's tagging accuracy in simulations.

This paper introduces Star-CDP, a dynamic programming algorithm for accurate cell lineage tree reconstruction from CRISPR-based data, showing improved performance over existing methods.

The paper uses long-read sequencing to analyze genomic and epigenomic changes in melanoma subclones, revealing parallel evolutionary paths and lineage-specific methylation patterns.

Severus detects and characterizes somatic structural variations in tumor genomes using long reads, outperforming existing methods in accuracy and revealing clinically relevant rearrangements.

The paper introduces a weighted version of the TREE-QMC method to improve species tree reconstruction robustness to gene tree errors and homology issues.

The paper models gene expression adaptation in tumor subclones using stochastic processes and finds non-genetic mechanisms drive subclonal evolution and treatment response.

This paper introduces Lemur and Magnet, lightweight tools for accurate taxonomic profiling of long-read metagenomic datasets, showing they run efficiently on laptops.

This paper introduces Sgootr, a method to infer tumor lineage trees from single-cell methylation data, revealing metastatic progression models and identifying lineage-informative CpG sites.

SCOPE infers population structure in large genomic datasets efficiently and accurately, outperforming existing methods in speed while maintaining comparable accuracy.

This paper introduces Exact-RFS-2, a polynomial-time algorithm for optimal supertree construction under the Robinson-Foulds criterion, and GreedyRFS, a heuristic that improves accuracy over existing methods.

ASTRAL-Pro improves species tree inference by handling gene duplication and loss, outperforming existing methods in complex scenarios.