Kathleen E. Houlahan

The Landscape of Prostate Tumour Methylation

This study maps epigenomic heterogeneity in prostate cancer by analyzing 3,001 methylomes and identifies four subtypes with distinct clinical and molecular features.

The human pangenome reference reduces ancestry-related biases in somatic mutation detection

This study benchmarks somatic mutation detection using the human pangenome reference and finds improved accuracy, especially in East Asian individuals.

Deletions Rate-Limit Breast and Ovarian Cancer Initiation

The paper identifies genomic deletions as the rate-limiting mutational processes in breast and ovarian cancer initiation, requiring 1-3 deletions for tumor development.

High-confidence structural predictions of extrachromosomal DNA with ecDNAInspector

ecDNAInspector identifies high-confidence ecDNA structures from WGS data, linking them to clinical and molecular features in breast cancer.

Temporal and spatial composition of the tumor microenvironment predicts response to immune checkpoint inhibition

The paper uses spatial imaging and computational analysis to identify features in metastatic tumors that predict response to immune checkpoint inhibition in TNBC patients.

BPG: Seamless, Automated and Interactive Visualization of Scientific Data

BPG is an R package that generates publication-quality, customizable plots and offers an interactive web tool for figure customization and integration with computational pipelines.

Combining accurate tumour genome simulation with crowd-sourcing to benchmark somatic structural variant detection

The paper benchmarks somatic structural variant detection methods using synthetic tumors and crowd-sourced submissions, finding that ensembles do not always outperform individual methods.

Valection: Design Optimization for Validation and Verification Studies

Valection optimizes the selection of verification candidates to estimate error profiles in genomics studies by evaluating different strategies on synthetic data.

Accurate Reference-Free Somatic Variant-Calling by Integrating Genomic, Sequencing and Population Data

S22S is a reference-free method for somatic variant calling that uses genomic and population data to accurately identify SNVs without matched normal samples.

Germline Contamination and Leakage in Whole Genome Somatic Single Nucleotide Variant Detection

The paper quantifies germline leakage in somatic SNV detection across 259 datasets and introduces a tool to correct it, finding low leakage rates that can be further reduced with pre-filtering.