scATAC-seq

IRF8 configures enhancer landscape in postnatal microglia and directs microglia specific transcriptional programs

This study shows IRF8 regulates enhancer landscapes and transcriptional programs in postnatal microglia, affecting their identity and response to disease.

Probabilistic tensor decomposition extracts better latent embeddings from single-cell multiomic data

SCOIT, a probabilistic tensor decomposition framework, improves latent embeddings from single-cell multiomic data, enhancing clustering and cross-omics analysis.

MOCHA: Advanced statistical modeling of scATAC-seq data enables functional genomic inference in large human disease cohorts

MOCHA improves scATAC-seq analysis by addressing technical and biological challenges, enabling better gene regulatory insights in human disease.

ShinyMultiome.UiO: An interactive open-source framework utilizing Seurat Objects for visualizing single-cell Multiomes

ShinyMultiome.UiO provides an interactive web tool for visualizing single-cell Multiome data using Seurat objects, enabling collaborative analysis and public access.

Single-cell multiome regression models identify functional and disease-associated enhancers and enable chromatin potential analysis

SCARlink predicts gene expression from chromatin accessibility in single-cell multiome data, identifies enhancers, and enables chromatin potential analysis for developmental trajectories.

Multimodal single-cell analysis of non-random heteroplasmy distribution in human retinal mitochondrial disease

The paper uses multimodal single-cell sequencing to show non-random distribution of a pathogenic mtDNA variant in retinal cells of a MELAS patient.

Early acquisition of S-specific Tfh clonotypes after SARS-CoV-2 vaccination is associated with the longevity of anti-S antibodies

The paper investigates how early acquisition of S-specific Tfh clonotypes after SARS-CoV-2 vaccination correlates with sustained anti-S antibody levels.

Ensemble deep learning of embeddings for clustering multimodal single-cell omics data

SnapCCESS improves clustering of multimodal single-cell omics data by integrating multiple data modalities using an ensemble deep learning framework.

A generic reference defined by consensus peaks for scATAC-seq data analysis

The paper constructs a generic chromatin accessibility reference (cPeaks) from bulk ATAC-seq data to improve scATAC-seq analysis and cell type identification.

SIMBA: SIngle-cell eMBedding Along with features

SIMBA is a graph embedding method that jointly embeds single cells and their features into a common space, enabling diverse single-cell analysis tasks.

Widespread enhancer co-activity identified by multimodal single cell analysis

The paper identifies widespread enhancer co-activity in human lymphoblastoid cells using scATAC-seq and scRNA-seq, revealing correlations between enhancer activity and gene expression.

Dictionary learning for integrative, multimodal, and scalable single-cell analysis

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.

Unsupervised Contrastive Peak Caller for ATAC-seq

The paper introduces an unsupervised contrastive learning method for ATAC-seq peak calling that outperforms existing methods using replicates and annotations.

An interwoven network of transcription factors, with divergent influences from FoxP3, underlies Treg diversity

The paper defines the Treg regulatory network using single-cell chromatin accessibility and machine learning, revealing FoxP3's limited role in shaping Treg diversity.

RNA- and ATAC-sequencing Reveals a Unique CD83+ Microglial Population Focally Depleted in Parkinson's Disease

The paper uses single-nucleus RNA- and ATAC-sequencing to identify a CD83+ microglial subpopulation depleted in Parkinson's disease, with implications for neuronal vulnerability.

Integrative single-nucleus multi-omics analysis prioritizes candidate cis and trans regulatory networks and their target genes in Alzheimers disease brains

This study uses single-nucleus multi-omics data to identify cis and trans regulatory networks and their target genes in Alzheimer's disease brains.

Single-cell chromatin accessibility of developing murine pancreas identifies cell state-specific gene regulatory programs

This study uses single-nucleus ATAC-sequencing to analyze chromatin accessibility and RNA expression in developing mouse pancreas, identifying gene regulatory programs and transcription factors involved in cell fate determination.

Matrix prior for data transfer between single cell data types in latent Dirichlet allocation

The paper introduces a matrix prior for latent Dirichlet allocation to improve cell type detection in small scATAC-seq datasets by leveraging information from existing data.

The single-cell epigenetic regulatory landscape in mammalian perinatal testis development

The paper uses scATAC-Seq to analyze chromatin accessibility in mouse developing testis, identifying regulatory elements, transcription factors, and GWAS-associated targets.

A multi-omics atlas of the human retina at single-cell resolution

This paper presents a comprehensive single-cell multi-omics atlas of the human retina, integrating RNA-seq and ATAC-seq data to identify cell-type-specific cis-element-gene relationships and transcription factor regulons.

scART: recognizing cell clusters and constructing trajectory from single-cell epigenomic data

scART is a tool for analyzing scATAC-seq data that identifies cell clusters and constructs developmental trajectories, demonstrating effectiveness in mouse embryonic forebrain data.

Tensor Decomposition Discriminates Tissues Using scATAC-seq

This study uses tensor decomposition to address data sparsity in scATAC-seq and identifies tissue-specific patterns and gene associations.

Depicting pseudotime-lagged causality across single-cell trajectories for accurate gene-regulatory inference

This paper introduces DELAY, a deep learning method for inferring gene-regulatory networks from single-cell data, showing improved performance over existing methods in identifying causal relationships.

Chromatin access regulates the formation of Muller glia-derived progenitor cells in the retina

This study shows that SAHH and HMTs regulate chromatin access in chick retinas to reprogram Muller glia into progenitor cells, but not in mouse retinas.

InClust+: the multimodal version of inClust for multimodal data integration, imputation, and cross modal generation

InClust+ extends the inClust framework to handle multimodal data integration, imputation, and cross-modal generation, showing performance comparable to existing tools.

An atlas of gene regulatory networks for memory CD4+ T cells in youth and old age

The paper constructs an atlas of gene regulatory networks for memory CD4+ T cells in young and old mice, revealing age-related changes in transcription factor control and cell-cell communication.

Type I interferon dynamics determines memory B cell epigenetic identity in chronic viral infection

The paper identifies type I interferon dynamics as a key factor shaping memory B cell development during chronic viral infection and shows that early IFNAR-1 blockade can reverse chromatin changes.

Multi-task learning from single-cell multimodal omics with Matilda

Matilda is a multi-task learning method that integrates single-cell multimodal omics data by performing data simulation, dimension reduction, cell type classification, and feature selection.

Destin2: integrative and cross-modality analysis of single-cell chromatin accessibility data

Destin2 improves cross-modality analysis of scATAC-seq data by integrating multiple epigenomic features for dimension reduction, clustering, and trajectory inference.

The pseudokinase Trib1 regulates the transition of exhausted T cells to a KLR+ CD8+ effector state and its deletion improves checkpoint blockade

This study shows that deleting Trib1 shifts exhausted T cells to a KLR+ CD8+ effector state, enhancing viral clearance and checkpoint inhibitor response.