Orit Rozenblatt–Rosen

This paper evaluates combining expression-based surrogate variables and genotype-based principal components in differential expression analysis, finding the combined approach improves replicability and biological recall in ALS datasets.

The paper introduces CellMAPP and CHART to analyze multiplexed antibody imaging data, revealing modular morphological programs in response to genetic perturbations.

Perturb-ME combines CRISPR screening and single-cell profiling to identify regulatory modules governing gene programs in melanoma.

SCALLOPS improves processing of optical pooled screens by enabling efficient alignment and analysis of large-scale image data, demonstrating superior performance over existing methods.

Soma-seq measures both RNA and intracellular proteins in single human brain cells, revealing protein states linked to transcriptional programs in Alzheimer's disease.

The paper introduces PerturbPair, a platform integrating transcriptomic and optical screens to map macrophage regulatory networks, revealing cross-modal relationships and disease-relevant gene programs.

This paper develops a platform for longitudinal imaging and transcriptomics of live cells, revealing adaptive drug-resistant states and key drivers of cellular function through integrated analysis.

This study uses dynamic caging to link live-cell behavior with transcriptional responses across perturbations, revealing new insights into immune and inflammatory gene regulation.

This paper develops computational tools for allelic imbalance analysis using single-nucleus RNA-seq and demonstrates their application in a Parkinson's disease cohort.

The paper develops a framework to decode TLS maturation in NSCLC using spatial omics data and deep learning, identifying two distinct spatial ecosystems linked to patient outcomes.

The paper builds a dictionary of human intestinal organoid responses to 81 secreted niche factors using scRNA-seq, mapping perturbations and identifying cell type-specific pathways in an IBD context.

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

SpatialAgent integrates large language models with dynamic tool retrieval, multimodal interpretation, and claim verification to automate end-to-end spatial biology workflows from gene-panel design to tissue annotation and hypothesis generation.

This study creates a single-nucleus and spatial transcriptomic atlas of the COVID-19 liver, revealing cellular and functional disruptions associated with organ damage.

PerturbView enables highly multiplexed optical pooled screens in primary cells and tissues by improving barcode amplification, revealing regulators of NFκB signaling and enabling spatial transcriptomics integration.

The paper maps cellular changes in the aging human brain and identifies altered multicellular communities in Alzheimer's disease using single nucleus RNA-seq and bulk RNA-seq data.

SCHAF generates spatially resolved single-cell transcriptomes from H&E histology images using vision transformers and adversarial learning, showing good agreement with ground-truth data.

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

The paper uses Perturb-seq to systematically study 1,130 E3 ligases and their roles in inflammatory responses in dendritic cells, revealing co-functional modules and genetic interactions.

The paper identifies cell-type and cell-subtype specific eQTLs in aging human cortex, revealing variant effects on gene expression and disease associations.

The paper develops a method for single nucleus RNA-Seq from FFPE tissues and applies it to a human lung adenocarcinoma sample.

The paper benchmarks a new low-cost sequencing by synthesis method for scRNA-seq, showing comparable results to existing technologies and enabling cost-effective large-scale applications.

SM-Omics is a platform that combines spatial transcriptomics and proteomics to analyze tissue samples at scale.

This study uses single-cell RNA-sequencing to analyze fetal bone marrow development and identifies disruptions in hematopoiesis in Down syndrome.

The paper identifies obesity-related TREM2high macrophages in diabetic mouse and human kidney through single-cell transcriptomics and cross-species comparison.

This study constructs a single-cell and spatial atlas of the choroid plexus in developing and adult mice, revealing cell types, regional gene expression, and cell-cell interactions.

This study identifies transcriptional states in mCRPC that mediate treatment resistance, including AR splicing heterogeneity, TGF-β signaling, and immune infiltration patterns.

The paper uses Perturb-CITE-Seq to identify novel immune evasion mechanisms in cancer by analyzing multi-modal single-cell data from patient-derived models.

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