Farhia Kabeer

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

cfClone, a Bayesian model, deconvolves cfDNA whole-genome sequencing using scWGS-derived haplotype-specific clone copy-number profiles to estimate tumour fraction, clonal prevalence, and flag missed clones.

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

The paper introduces a scalable Bayesian method for phylogenetic tree inference from single-cell whole genome sequencing data, demonstrating its application on three datasets.

GeneVector uses mutual information-based dimensionality reduction to identify transcriptional programs and classify cell types across single-cell RNA-seq datasets.

Epiclomal clusters sparse single-cell DNA methylation data and imputes missing values, outperforming non-probabilistic methods and revealing sub-clonal methylation patterns in tumour genomes.

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.