Evan M. Murray

SlideCNA: Spatial copy number alteration detection from Slide-seq-like spatial transcriptomics data

SlideCNA detects spatial copy number alterations from Slide-seq data to identify sub-clones in metastatic breast cancer.

An atlas of healthy and injured cell states and niches in the human kidney

The paper creates a high-resolution cellular atlas of healthy and injured kidney cell states and niches using single-cell and spatial technologies, identifying molecular signatures and pathways related to kidney injury.

The cell type composition of the adult mouse brain revealed by single cell and spatial genomics

Whole-brain snRNA-seq paired with Slide-seq assigns cell types to each mouse neuroanatomical structure; most clusters need at least three markers to be defined uniquely.

TACCO: Unified annotation transfer and decomposition of cell identities for single-cell and spatial omics

TACCO is a framework for annotating cell identities in single-cell and spatial omics data, excelling in speed and performance across datasets.

Cell type-specific inference of differential expression in spatial transcriptomics

The paper introduces a statistical method to detect cell type-specific differential gene expression in spatial transcriptomics data and validates it using simulations and real datasets.

Single-cell multiomics atlas of organoid development uncovers longitudinal molecular programs of cellular diversification of the human cerebral cortex

The paper presents a single-cell multiomics atlas of human cortical organoid development, revealing molecular programs of cellular diversification and identifying human-specific gene roles in lineage establishment.

High Resolution Slide-seqV2 Spatial Transcriptomics Enables Discovery of Disease-Specific Cell Neighborhoods and Pathways

This study uses Slide-seqV2 to identify disease-specific cell neighborhoods and pathways in human and mouse kidneys.

Detection of allele-specific expression in spatial transcriptomics with spASE

The paper introduces spASE, a method to detect spatial patterns in allele-specific expression from spatial transcriptomics data, showing it can identify cell type-specific effects in mouse hippocampus.

Dissecting Mammalian Spermatogenesis Using Spatial Transcriptomics

This study uses spatial transcriptomics to create a spatial atlas of testis gene expression, identifying spatially segregated spermatogonial populations and disruptions in diabetic testes.

Robust decomposition of cell type mixtures in spatial transcriptomics

This paper introduces RCTD, a method to decompose cell type mixtures in spatial transcriptomics, improving cell type assignment and enabling discovery of spatially dependent gene expression.

Compressed sensing for imaging transcriptomics

The paper introduces CISI, a method that uses compressed sensing to efficiently recover spatial gene expression data from composite measurements, achieving high efficiency and scalability.

Sensitive spatial genome wide expression profiling at cellular resolution

The paper improves Slide-seq technology to enhance mRNA capture sensitivity, enabling high-resolution spatial transcriptomics in mouse tissues.

Slide-seq: A Scalable Technology for Measuring Genome-Wide Expression at High Spatial Resolution

Slide-seq measures genome-wide expression in complex tissues at 10-micron resolution.