Harinder Singh

Sequential and coordinated control of human plasma cell differentiation by IRF4 and BLIMP1 associated with a discriminating ISRE/EICE motif lexicon

This study identifies an ISRE/EICE motif lexicon that distinguishes IRF4 and BLIMP1 binding during plasma cell differentiation, revealing a temporally ordered regulatory mechanism.

Interpretable machine learning coupled to gene regulatory networks uncovers subcircuits underlying cell fate decisions

FOCAL couples interpretable machine learning with gene regulatory networks to identify regulatory subnetworks underlying cell fate decisions in B and T cells.

FlowMap: Geometry Dynamics Consistent Embedding of RNA Velocity for Interpretable Cellular Trajectories

FlowMap jointly models cellular states and dynamics in a geometric framework, recovering interpretable trajectories and developmental patterns from single-cell RNA sequencing data.

BLIMP1 shapes germinal center B cell clonal diversity by gating chromatin accessibility during light-to-dark zone transition

This study shows Blimp1 restricts clonal dominance in germinal center B cells by controlling chromatin accessibility and BCR signaling during the light-to-dark zone transition.

Regulatory network architecture constrains inflammatory responses in tissue-resident alveolar macrophages

The paper investigates gene regulatory networks in alveolar macrophages, finding that tissue-resident macrophages have more restrained inflammatory responses due to a stabilizing network involving PU.1 and CEBP/β.

Epidermal Resident Memory T Cell Fitness Requires Antigen Encounter in the Skin

This study shows that antigen encounter in the epidermis enhances TRM persistence and proliferation through TGF{beta} signaling and TGF{beta}RIII expression.

HALO: Hierarchical Causal Modeling for Single Cell Multi-Omics Data

HALO models temporal causal relations in single-cell multi-omics data by distinguishing coupled and decoupled latent representations, revealing lineage specification dynamics in AT2 cells.

Expanding the DNA Motif Lexicon of the Transcriptional Regulatory Code

The paper expands the DNA motif lexicon of transcriptional regulatory code by identifying composite elements and using a deep learning model to predict their activity and impact of variants.

Multi-scale gene regulatory networks for resolving transcription factor and autoimmune variant impacts on human B cell fate dynamics

Altered AP-1, RUNX, and EGR chromatin dynamics drive fibrotic lung disease

The paper identifies transcription factor networks driving fibrotic lung disease using multiomic single-cell data from SSc-ILD and control lungs.

Population-level comparisons of gene regulatory networks modeled on high-throughput single-cell transcriptomics data.

This paper introduces SCORPION, a tool for reconstructing gene regulatory networks from single-cell RNA-seq data, showing it outperforms existing methods and detects consistent regulatory differences in colorectal cancer.

COVID-19db linkage maps of cell surface proteins and transcription factors in immune cells

The paper develops a database linking cell surface proteins and transcription factors in immune cells using CITE-seq data from COVID-19 patients and healthy controls.

scTriangulate, a game-theory based framework for optimal solutions of uni- and multimodal single-cell data

scTriangulate identifies high-confidence cell populations and modality-specific subtypes by combining clustering results from uni- and multimodal single-cell data using a game-theory framework.

Essential Regression - a generalizable framework for inferring causal latent factors from multi-omic human datasets

Essential Regression infers causal latent factors from multi-omic human datasets, outperforming existing methods in prediction performance and enabling causal inferences.

Diverse digital and fuzzy composite transcriptional elements are prevalent features of mammalian cis-regulomes

The paper identifies and characterizes diverse composite transcriptional elements (CEs) in mammalian cis-regulomes, revealing digital and fuzzy configurations with distinct regulatory properties.

SPaRTAN, a computational framework for linking cell-surface receptors to transcriptional regulators

SPaRTAN links cell-surface receptors to transcription factors using CITE-seq data and cis-regulatory information, revealing novel receptor-TF relationships in immune and tumor cells.

Inferring cellular trajectories from scRNA-seq using Pseudocell Tracer

Pseudocell Tracer infers cellular trajectories from scRNA-seq data by simulating pseudocells in a virtual cell-state axis, revealing transcription factor dynamics during B cell immunoglobulin class switch recombination.

Organizational properties of a functional mammalian cis-regulome

The paper constructs a functional cis-regulome for activated murine B-cells using FAIRE-seq, STARR-seq, and Hi-C, revealing long-range enhancer-promoter interactions and complex transcription factor codes.

Single cell transcriptomic analysis identifies Langerhans cells immunocompetency is critical for ability to induce tolerogenic T cells.

The paper identifies that Langerhans cells (LCs) upregulate a tolerogenic gene module during migration, which is critical for inducing regulatory T cells.

DoubletDecon: Cell-State Aware Removal of Single-Cell RNA-Seq Doublets

DoubletDecon identifies and removes doublets in scRNA-Seq data using deconvolution and cell-state gene expression analysis, improving cell state delineation.