Linas Mažutis

The paper introduces Suco and Compocyte to classify immune cells from 3,965 patients, identifying new macrophage and monocyte states and T cell memory erosion in metastases.

This paper introduces a semi-permeable capsule technology for high-throughput single-cell -omics, demonstrating its utility in scRNA-Seq of hematopoietic disorders and uncovering transcriptome changes in AML.

The paper analyzes transcriptomic changes in metastatic pancreatic cancer using a patient's autopsy data to identify site-specific gene programs and clonal phylogeny.

The paper introduces a method to link single-cell imaging and gene expression data through multimodal droplet barcoding, identifying genes correlated with phenotypic features.

Decipher is a deep generative model that integrates single-cell RNA-seq data to visualize and characterize transitions between normal and perturbed cell states across different diseases.

This paper introduces Bascet and Zorn, tools for scalable single-cell metagenomic analysis, demonstrating their utility on mock and human saliva samples.

The paper introduces inDrops-2, a cost-efficient scRNA-seq platform that profiles clinical samples with sensitivity comparable to commercial systems and demonstrates its utility in analyzing lung carcinoma samples.

The paper uses single-cell analysis to study how cell surface antigen expression changes in treatment-resistant prostate cancer, revealing transcriptional heterogeneity and shared gene regulatory networks between NEPC and SCLC.

This paper introduces a high-throughput RNA cytometry method using semi-permeable microcapsules to enable digital profiling of single-cell gene expression.

The paper defines a shared differentiation trajectory of CD8 T cell dysfunction across cancer and infection using ATAC-seq and RNA-seq data from multiple studies.

This study identifies R47H-TREM2 mutation-induced proinflammatory microglial states in human AD and tauopathy mice, showing Akt pathway involvement and potential therapeutic targets.

Palantir models cell fate as a probabilistic process using entropy to analyze differentiation trajectories in human hematopoiesis, identifying key transcription factors and terminal states.

MAGIC improves single-cell RNA-seq data by imputing missing values and revealing gene-gene interactions through a diffusion-based method.