Austin Hartman

Genome-scale CRISPRi perturb-seq in 22 million primary human CD4+ T cells maps stimulation-specific regulators and links perturbation signatures to T cell states and autoimmune genetics.

This paper identifies methods to achieve ultra-large DNA integrations (>10 kb) in human cells with high efficiency using optimized templates and delivery strategies.

The paper identifies off-target effects in CRISPRi Perturb-seq experiments by analyzing transcriptional similarity between on-target and off-target guide effects.

CRISPR-All enables genome-scale, combinatorial genetic perturbations in human cells, revealing additive functional improvements through multiplexed modifications.

Phospho-seq integrates phosphorylated protein profiling with scATAC-seq and scRNA-seq to study cell signaling and gene regulation in single cells.

This paper designs novel transcription factors using evolutionary principles to generate T cell states with enhanced functionality.

The paper develops a meta-analysis method to identify reproducible differentially expressed genes across single-cell transcriptomic case-control studies and finds shared genes across neurodegenerative diseases.

This study compares six in situ gene expression profiling methods using mouse brain datasets, highlighting challenges in sensitivity metrics and proposing new metrics to improve analysis.

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.

Dictionary learning enables assumption-free cross-modality single-cell mapping via multi-omic bridge datasets and scales single-modality integration to millions of cells in under an hour via atomic sketching.

The paper introduces CPA-Perturb-seq, a multiplexed perturbation screen dataset, and uses it to identify polyA site regulators and their functional properties.