Ciara H. O’Flanagan

G4SCOPE predicts chromatin G-quadruplex occupancy from DNA sequence, revealing epigenetic differences in BRCA1 and BRCA2 deficient cells.

Serval is a modular framework for decoding spatial transcriptomics data that introduces Cosine, a method improving transcript recovery and correlation with expression references.

This paper develops a framework to analyze chromosomal mutational patterns at single-cell resolution, revealing drug-induced mutational signatures in human tissues.

This study shows that somatic copy number mutations (CNA) influence metastatic fitness in breast cancer by mediating transcriptional changes and affecting clone survival in different sites.

The paper analyzes copy number alterations in breast epithelial cells from BRCA mutation carriers and wildtype individuals, finding lineage-specific CNAs that mirror cancer genomes.

The paper identifies genomic and non-genomic contributions to drug resistance in triple negative breast cancer using single cell transcriptomics and copy number data.

PhylEx reconstructs clonal structure by integrating bulk DNA-seq and scRNA-seq data, outperforming existing methods in clonal-tree reconstruction and mutation clustering.

ExSeq enables multiplexed RNA mapping at nanoscale resolution by expanding biological specimens for in situ sequencing.

This study identifies transcriptional stress responses in single-cell RNA-seq data from dissociated tumour tissues, showing that collagenase digestion induces a conserved stress response minimized by cold active protease.

clonealign integrates single-cell RNA and DNA sequencing data from cancer samples to identify clone-specific gene expression patterns and dysregulated pathways.

CellAssign probabilistically assigns cell types to scRNA-seq data, revealing spatiotemporal dynamics in human cancers like ovarian and follicular lymphoma.