Rahul Satija

VIPerturb-seq enables genome-wide CRISPR perturbation screens using probe-based detection, improving throughput and efficiency for single-cell analysis.

Pan-human Azimuth maps diverse human cells into a unified hierarchical typology, enabling cross-tissue comparisons and spatial transcriptomic annotation.

The paper introduces the SenNet Portal, a resource for senescent cell data and tools, and discusses its usage and future developments.

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

The paper introduces scSLIDE, a framework that generates sample-level embeddings from single-cell data to analyze variation across samples in disease and development.

The paper shows that cortical layering in tetrapods follows conserved developmental principles, with mammals displaying an inverted layer order.

This paper introduces RNA fingerprinting, a method to map transcriptional responses to perturbations using reference dictionaries, showing accurate single-cell assignments and broad biological applications.

The paper presents an iterative framework to identify mTOR signaling regulators using multimodal single-cell data and validates novel regulators through experimental testing.

This paper describes the construction and usage of the Human Reference Atlas (HRA) v2.0, which integrates multiscale data across 36 organs and provides tools for analysis and visualization.

The paper uses Perturb-seq to systematically identify signaling regulator targets across multiple cell lines and contexts, introducing Mixscale to improve analysis and infer pathway activation changes.

The paper examines gene expression variation in rice under salinity stress, finding trans-eQTLs dominate and cis-trans reinforcement is more common than compensation.

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

PanSci, a single-cell transcriptome atlas of over 20 million cells throughout the mouse lifespan, unveils the temporal architecture of aging-associated cellular population dynamics, organ-specific immune cell shifts, and the lymphocytes role in organismal aging.

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 identifies TET2-mutant clonal hematopoiesis in thyroid cancer microenvironments and shows that TGFβ signaling from these macrophages mediates resistance to BRAF/MEK inhibition, with TGFβ inhibition restoring sensitivity.

SEraster reduces computational resource needs for spatial omics analysis by aggregating cell data into spatial pixels, enabling efficient analysis of large datasets.

This study uses single-cell multi-omics to map genotype-to-phenotype relationships in VEXAS syndrome, identifying PERK pathway activation as a therapeutic target.

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 miloDE, a cluster-free method for differential expression testing in single-cell RNA sequencing data, improving sensitivity and specificity by avoiding discrete clustering.

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

The paper characterizes antigen-specific CD8+ T cells post-SARS-CoV-2 vaccination and infection using multimodal sequencing, identifying unique biomarkers and clinical predictors.

The paper introduces CaRPool-seq, a method using Cas13 for combinatorial RNA perturbations in single cells, and applies it to study myeloid differentiation regulators in AML.

The paper introduces scCUT&Tag-pro and scChromHMM to analyze chromatin states in single cells, showing their ability to characterize dynamic changes and regulatory priming across immune cell types.

This paper introduces NTT-seq, a method to measure multiple chromatin features at single-cell resolution, and demonstrates its application in immune cells.

The paper develops a multi-omic single-nucleus sequencing method and framework to analyze regulatory genome diversity in human cortical cells and link it to disease risk variants.

This study evaluates statistical error models for scRNA-seq, finding that negative binomial models are more appropriate than Poisson for most datasets due to overdispersion.

geneBasis selects an optimal gene panel from scRNA-seq data by iteratively adding genes that maximize manifold distance, outperforming existing methods in resolving cell types and states.

Signac extends Seurat with a ChromatinAssay for single-cell chromatin and multimodal analysis, adds modified TF-IDF weighting, peak-gene linkage and mitochondrial-variant clonotyping, and scales to 733,526 cells.