Andrew McPherson

Serval: A modular framework for decoding imaging based spatial transcriptomics data

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

Recurrent non-canonical proteoforms in acute myeloid leukemia identified by integrative proteogenomics

The paper identifies recurrent non-canonical proteoforms in AML using integrative proteogenomics, revealing 5,849 unannotated proteoforms, including 1,987 with no homology to annotated proteins.

scPlOver: inferring DNA content from amplification-free single-cell WGS using fragment overlaps

scPlOver infers DNA content from single-cell WGS data using fragment overlaps, improving accuracy in identifying high DNA content cells in ovarian cancer.

Evolution of oncogene amplification across 86,000 cancer cell genomes

The paper analyzes the evolutionary trajectories of high-level copy-number amplifications in cancer cell genomes to distinguish between extrachromosomal and intrachromosomal amplification mechanisms.

Tracking clonal evolution of drug resistance in ovarian cancer patients by exploiting structural variants in cfDNA

This study tracks clonal evolution of drug resistance in ovarian cancer using structural variants in cfDNA, finding polyclonal resistance with dominant high-fitness clones and genomic features linked to drug resistance.

End-to-end proteogenomics for discovery of cryptic and non-canonical cancer proteoforms using long-read transcriptomics and multi-dimensional proteomics

The paper introduces ProteomeGenerator3, an end-to-end proteogenomics method that detects non-canonical proteoforms in cancer using long-read transcriptomics and multi-dimensional proteomics.

Ongoing genome doubling promotes evolvability and immune dysregulation in ovarian cancer

This study shows that ongoing whole-genome doubling in ovarian cancer promotes cell diversity and immune dysregulation through chromosomal instability and quiescent states.

Complementary modes of resistance to EGFR TKI in lung adenocarcinoma through MAPK activation and cellular plasticity

This study identifies MAPK activation and cellular plasticity as complementary resistance mechanisms to EGFR TKI in lung adenocarcinoma using single-nuclei RNA sequencing and clinical data.

Disrupted priming within draining lymph nodes drives immune quiescence in gastric cancer

The paper identifies impaired T cell priming and KLF2-dependent quiescence in gastric cancer draining lymph nodes as mechanisms limiting immune responses.

CINner: modeling and simulation of chromosomal instability in cancer at single-cell resolution

CINner models chromosomal instability in cancer, showing how selection parameters and WGD influence tumor progression and heterogeneity.

Inferring active mutational processes in cancer using single cell sequencing and evolutionary constraints

This paper introduces ArtiCull, a method to analyze single-cell whole-genome sequencing data to distinguish active from historical mutational processes in cancer, revealing temporal and spatial patterns in mutational signatures.

Luminal breast epithelial cells from wildtype and BRCA mutation carriers harbor copy number alterations commonly associated with breast cancer

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.

Cancer phylogenetic tree inference at scale from 1000s of single cell genomes

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: Identification of transcriptional programs using dense vector representations defined by mutual information.

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

TCRi: Information theoretic metrics for single cell RNA and TCR sequencing in cancer

This paper introduces TCRi, an information theoretic framework to analyze TCR and gene expression data from cancer patients, showing improved characterization of clonotypes and their phenotypic changes post-therapy.

Expansion Sequencing: Spatially Precise In Situ Transcriptomics in Intact Biological Systems

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

Dissociation of solid tumour tissues with cold active protease for single-cell RNA-seq minimizes conserved collagenase associated stress responses

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: statistical integration of independent single-cell RNA & DNA-seq from human cancers

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

Probabilistic cell type assignment of single-cell transcriptomic data reveals spatiotemporal microenvironment dynamics in human cancers

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

Resource: Scalable whole genome sequencing of 40,000 single cells identifies stochastic aneuploidies, genome replication states and clonal repertoires

Computational proteogenomic identification and functional interpretation of translated fusions and micro structural variations in cancer

The paper introduces a computational framework integrating genomic, transcriptomic, and proteomic data to identify and interpret translated fusions and micro structural variations in cancer, finding many novel peptides and private aberrations in breast cancer.

The interface of malignant and immunologic clonal dynamics in high-grade serous ovarian cancer

The paper analyzes the interaction between tumor and immune clones in ovarian cancer, finding that immune contexture patterns mirror malignant spread and that foldback inversions correlate with poor outcomes.

deStruct: Accurate Rearrangement Detection using Breakpoint Specific Realignment

deStruct improves breakpoint prediction by using specific realignment and clustering, achieving higher sensitivity and specificity than existing tools on simulated data.