Nir Yosef

Pycea provides a toolkit for analyzing single-cell lineage tracing data, integrating with Scanpy and offering visualization and statistical methods for lineage trees.

The paper introduces CSDE, a method that improves differential expression analysis in spatial transcriptomics by incorporating expert feedback to mitigate preprocessing biases.

The paper presents the Human Gut Cell Atlas v1.0, a unified reference of gut cell diversity, revealing how tissue structure influences cellular composition and enabling disease and organoid analysis.

Prime-editing lineage trees for 16 mouse embryos (E7.5 to E10.0, >1.4 million cells) quantify fate restriction timing, progenitor numbers and lineage relationships, and are reproducible across replicate embryos.

ResolVI improves spatial transcriptomics by correcting molecule misassignment and batch effects, enhancing cell state distinction and cross-dataset integration.

immgenT creates a comprehensive T-cell molecular atlas across mouse organs and disease states, identifying 8 lineages and 107 clusters using deep generative models and integrating external datasets.

This study uses spatial transcriptomics and lineage tracing to show how tumor subclones drive microenvironmental changes that promote metastasis in a mouse model.

The paper shows preselection CD4+CD8+ thymocytes undergo gene expression changes linked to reduced TCR responsiveness and impaired CD4 fate gene upregulation, connecting these changes to T cell lineage commitment.

NovaClone improves clonal and subclonal genotyping in single-cell lineage tracing by addressing technical artifacts and providing quality control metrics.

Harreman identifies metabolic crosstalk in spatial transcriptomics data by analyzing co-localized metabolite transporter expression, revealing tissue-specific metabolic exchanges in human and mouse models.

The paper benchmarks large language models for cell-type and gene set annotation using AnnDictionary, finding high accuracy in cell-type annotation and strong functional gene set recovery.

MrVI is a deep generative model that identifies sample-level stratifications and cellular differences without prior cell-type grouping, applied to COVID-19 and IBD data.

The paper constructs a CAR-T cell functional atlas from over one million cells across 13 studies to link product composition with clinical response and identify sex- and age-dependent effects.

CytoVI is a deep generative model for antibody-based single cell technologies that improves integration, imputation, and analysis across different platforms and antibody panels.

Scvi-hub provides a platform for sharing and analyzing single-cell omics datasets using pre-trained models, enabling efficient tasks like visualization and annotation with reduced computational demands.

The paper profiles immune cell RNA and protein expression across tissues and age to identify tissue-specific and age-related immune signatures.

This paper introduces ConvexML, a fast and accurate method for estimating branch lengths in phylogenetic trees under irreversible mutation models, with applications to CRISPR/Cas9 lineage tracing data.

This study shows that aging microbiota impairs Treg cell function through TNF signaling, leading to inflammation and immune aging.

This paper introduces a homoplasy-based method to assess lineage tree reliability using Cas9-induced mutations, showing it outperforms parsimony in simulations.

PEtracer maps cell state and lineage dynamics in vivo with high spatial resolution using prime editing and multimodal imaging.

MEBOCOST infers metabolite-mediated cell communications from single-cell RNA-seq data, identifying known and novel interactions in mouse brown adipose tissue.

This study identifies PGAM as a negative regulator of Th17 pathogenicity using single-cell RNA-seq and metabolic flux analysis.

scVIVA is a deep generative model that integrates cell-intrinsic and neighboring gene expression to produce embeddings and gene profiles, revealing spatially restricted tumor-promoting endothelial cells and niche-associated T cell states in breast cancer.

This paper develops a Neighbor-Joining algorithm with theoretical guarantees for reconstructing phylogenies from CRISPR-Cas9 lineage tracing data, showing improved performance on simulated and real data.

The paper constructs enhancer-promoter interaction networks during neural differentiation and identifies their temporal dynamics and disease-associated variant enrichment using computational and experimental methods.

This study uses SCHEMATIC to analyze the molecular response of glioblastoma to EGFR inhibitors, identifying chemotype-specific programs and showing that combined EGFR/PI3K inhibition reduces adaptive transcription.

This paper evaluates sequence design strategies for perturbation MPRA using a computational framework and finds that random nucleotide shuffling outperforms other methods.

This paper introduces VI-VS, a framework for identifying conditionally dependent features in multiomic data while controlling false discovery rates.

This paper introduces veloVI, a deep generative model for RNA velocity analysis, showing improved data fit, consistency, and uncertainty quantification compared to existing methods.

popV improves cell-type annotation by providing uncertainty scores and reducing manual inspection through ensemble voting.