Andrew Adey

The paper identifies subtype-intermediate progenitor cells in pancreatic cancer with distinct epigenetic profiles linked to clinical outcomes and lineage reprogramming.

This study maps early postnatal DNA methylation dynamics in the mouse brain, revealing subtype-specific methylation changes and their disruption in Rett syndrome.

This study identifies RUNX1 as a key driver of tumor-immune hybrid cell invasion and dissemination in colorectal cancer, highlighting circulating hybrid cells as a biomarker for metastasis.

The paper introduces dominoSignal, a software tool that statistically tests differential cell signaling from single-cell data to infer changes in cell-cell communication networks.

This study identifies stem-monocytic AML as a distinct subtype resistant to venetoclax and shows that PU.1 inhibition synergizes with BCL2 blockade to enhance therapeutic response.

This study functionally characterizes mutant ASXL1 in human hematopoietic stem cells, showing it drives transcriptional activation and repression through interactions with BRD4 and MECOM, with implications for therapy.

This study identifies epigenetic and transcriptomic changes in the hippocampus and blood of an Alzheimer's mouse model before amyloidosis onset, suggesting blood methylation as a potential biomarker.

The paper introduces sciMETv3, a high-throughput single-cell DNA methylation profiling method, achieving 100-fold higher cell throughput and compatibility with multimodal assays.

The paper introduces txci-ATAC-seq, a high-throughput single-cell ATAC-seq method, and demonstrates its application across multiple tissues and genetic backgrounds.

The paper develops a framework to analyze scRNA-seq data and identify gene-regulatory networks linked to CD8 T cell exhaustion in tumor and viral infection contexts.

sciMET-cap reduces sequencing burden for single-cell methylation analysis while enabling accurate cell type assignment and near-complete methylome reconstruction.

PENCIL identifies phenotype-relevant cell subpopulations from single-cell data using a supervised learning framework with feature selection and trajectory prediction capabilities.

The paper identifies a dual state of Bmi1-expressing intestinal stem cells that drive epithelial development and tissue regeneration through dynamic Wnt signaling.

This study examines the functional effects of two patient-specific Tbr1 mutations on cortical development in mice, revealing both shared and distinct phenotypes.

The paper introduces Cas12a-Capture, a low-cost, scalable targeted sequencing method that reduces GC bias and improves variant calling accuracy.

This paper introduces a novel adaptor-switching strategy, s3, that significantly improves usable reads per cell in single-cell genomics assays while maintaining high-throughput capabilities.

The paper introduces sciMAP-ATAC, a method for spatially resolved single-cell chromatin accessibility profiling, and applies it to study cortical lamination, spatial trajectories, and ischemic infarct progression in mouse and human tissues.

Scissor identifies cell subpopulations from single-cell data correlated with specific phenotypes using clinical information, revealing biologically relevant subpopulations in lung and melanoma cancers.

The paper develops sci-LIANTI, a single-cell DNA sequencing method, to map meiotic crossovers and chromosome mis-segregation in hybrid mice, finding frequent mitotic segregation during meiosis.

The paper introduces an improved single-cell ATAC-seq method, scip-ATAC-seq, which enhances chromatin dynamics analysis in human corticogenesis organoids.

The paper presents a single-cell chromatin accessibility map of the mouse hippocampus using sci-ATAC-seq, identifies cell-type-specific regulatory networks, and provides a resource for future studies.

The paper uses single-cell DNA sequencing in non-human primates to show that chromosomal errors in embryos are encapsulated into micronuclei, fragmented, or excluded to prevent aneuploidy.

The paper introduces sci-MET, a scalable single-cell DNA methylation sequencing method, achieving 69% read alignment rates and successfully deconvolving a mixture of three human cell lines.

This paper introduces sci-RNA-seq, a combinatorial indexing method for single-cell RNA sequencing, and applies it to profile 42,035 C. elegans cells, identifying 27 cell types and their specific genes.

The paper introduces Cicero, a statistical method to link regulatory elements to target genes using single-cell chromatin accessibility data, and applies it to study myogenesis.