Andrew J. L. Roth

This study identifies a thymus-specific B-cell differentiation program linked to thymic B-cell lymphomagenesis through single-cell multiomics and spatial profiling.

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

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.

The paper uses multi-omic single-cell spatial techniques to study FL transformation, finding spatial shifts in B-cell neighborhoods and immunomodulatory interactions linked to disease progression.

This study uses a mouse model to identify a fibroblastic origin for DICER1 sarcomas and shows their potential to differentiate into rhabdomyoblastic or anaplastic sarcomas.

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.

PhyClone is a Bayesian method that reconstructs cancer phylogenies from bulk sequencing data, showing improved accuracy and scalability over existing methods.

This study identifies four molecular subtypes of Hodgkin lymphoma using multimodal data, revealing distinct clinical features and immune ecosystem dynamics.

CopyMix jointly infers cell clusters and copy number profiles from single-cell DNA sequencing data, avoiding clustering artifacts and parameter tuning.

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

ESQmodel evaluates single-cell segmentation quality using expression data and a prior belief of cellular composition to compute per-cell entropy.

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

SpatialSort is a Bayesian clustering method for spatial proteomics data that integrates spatial information and prior knowledge to improve cell population annotation.

The paper uses single-cell sequencing to study the evolution of follicular lymphoma and its microenvironment during transformation, finding gene programs and TME changes associated with progression.

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.

PyClone-VI infers cancer clonal structures from whole genome data efficiently and accurately, validated on PCAWG and TRACERx datasets.