scATAC-seq

Cobolt: Joint analysis of multimodal single-cell sequencing data

Cobolt integrates multi-modality single-cell data by providing a framework for joint analysis of gene expression and chromatin accessibility.

Benchmarking atlas-level data integration in single-cell genomics

BBKNN, Scanorama, and scVI lead complex scRNA-seq integration in a 38-setup, nine-task, 14-metric benchmark; highly variable gene selection helps, whereas scaling favors batch removal over bio-conservation.

Simultaneous CUT&Tag profiling of the accessible and silenced regulome in single cells

The paper describes a modified CUT&Tag protocol that profiles both active and repressive regulatory elements in single cells using computational signal deconvolution.

CoRE-ATAC: A deep learning model for the functional classification of regulatory elements from single cell and bulk ATAC-seq data

CoRE-ATAC is a deep learning model that classifies regulatory elements from ATAC-seq data, accurately predicting cis-RE functions across multiple cell types and identifying cell-specific variations in regulatory activity.

Contrastive Cycle Adversarial Autoencoders for Single-cell Multi-omics Alignment and Integration

This paper introduces a framework to align and integrate single-cell RNA-seq and ATAC-seq data, achieving higher accuracy than existing methods on both simulated and real data.

Assessing the multimodal tradeoff

The paper develops snATAK for preprocessing single-nucleus chromatin accessibility data and evaluates tradeoffs between multimodal assays.

Time series scRNAseq analysis in mouse and human informs optimization of rapid astrocyte differentiation protocols.

The paper uses scRNAseq data from mouse and human to identify candidate genes for glial fate specification and optimize astrocyte differentiation protocols.

Smart3-ATAC: a highly sensitive method for joint accessibility and full-length transcriptome analysis in single cells

Smart3-ATAC enables joint analysis of mRNA and chromatin accessibility in single cells with higher yield than existing droplet multiome methods.

Human and rat skeletal muscle single-nuclei multi-omic integrative analyses nominate causal cell types, regulatory elements, and SNPs for complex traits

The paper integrates snATAC-seq and snRNA-seq data from human and rat skeletal muscle to identify cell types, regulatory elements, and SNPs associated with complex traits.

MultiMAP: Dimensionality Reduction and Integration of Multimodal Data

MultiMAP integrates multimodal data by reducing dimensionality and preserving structure, outperforming existing methods in various tasks.

The three-dimensional chromatin structure of the major human pancreatic cell types reveals lineage-specific regulatory architecture of T2D risk

The paper uses 3D chromatin maps to identify cell-type-specific regulatory architecture of type 2 diabetes risk by analyzing pancreatic cell types.

Haplotype-aware single-cell multiomics uncovers functional effects of somatic structural variation

This paper introduces scNOVA, a method to analyze somatic structural variants in single-cell multiomics data, revealing their functional impacts on gene regulation and cancer pathways.

Integrated analyses of the single-cell ATAC-seq and RNA-seq reveal the epigenetic landscape of human ovarian aging

This study integrates single-cell ATAC-seq and RNA-seq to reveal the epigenetic and transcriptional changes in human ovarian aging, identifying key pathways and a predictive model for oocyte aging.

Gene regulatory networks controlling temporal patterning, neurogenesis and cell fate specification in the mammalian retina.

This study identifies gene regulatory networks controlling retinal development by integrating single-cell RNA and ATAC-seq data from mouse and human retinas, revealing transcription factors that regulate temporal patterning and cell fate.

Single-cell chromatin state analysis with Signac

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.

A cell atlas of chromatin accessibility across 25 adult human tissues

The paper creates a chromatin accessibility atlas across 25 adult human tissues, identifying over 750,000 cis-regulatory elements and linking them to gene regulatory programs and disease-associated variants.

DeepMAPS: Single-cell biological network inference using heterogeneous graph transformer

DeepMAPS infers biological networks from single-cell multi-omics data using a heterogeneous graph transformer, outperforming existing tools in cell clustering and pathway prediction.

Regulatory variants active in iPSC-derived pancreatic progenitor cells are associated with Type 2 Diabetes in adults

Copy-scAT: Deconvoluting single-cell chromatin accessibility of genetic subclones in cancer

Copy-scAT deconvolutes single-cell chromatin accessibility to infer genetic subclones in cancer, revealing how genetics influence chromatin profiles and subclonal phenotypes.

Integrated spatial multi-omics reveals fibroblast fate during tissue repair

The paper uses integrated spatial multi-omics to study fibroblast fate during tissue repair and defines mechanisms controlling cell fate in wound healing.

SMILE: Mutual Information Learning for Integration of Single Cell Omics Data

SMILE integrates single-cell omics data by learning discriminative representations through mutual information maximization, effectively removing batch effects and aligning diverse data types.

Integrative analysis of scRNAs-seq and scATAC-seq revealed transit-amplifying thymic epithelial cells expressing autoimmune regulator

The paper identifies transit-amplifying thymic epithelial cells expressing Aire and CD80 through integrative scRNA-seq and scATAC-seq analysis.

Comprehensive characterization of tissue-specific chromatin accessibility in L2 Caenorhabditis elegans nematodes

The paper presents the first single cell ATAC-seq study in C. elegans, identifying tissue-specific chromatin accessibility patterns aligned with existing RNA-seq data.

ShinyArchR.UiO: User-friendly, integrative and open-source tool for visualisation of single-cell ATAC-seq data using ArchR

ShinyArchR.UiO provides a user-friendly web interface for visualizing and analyzing scATAC-seq data using ArchR, enabling collaborative interpretation and open data sharing.

Single-cell DNA and RNA sequencing reveals the dynamics of intra-tumor heterogeneity in a colorectal cancer model

This study uses single-cell DNA and RNA sequencing to analyze intra-tumor heterogeneity dynamics in a mouse colorectal cancer model, finding increased RNA heterogeneity and decreased DNA heterogeneity after transplantation.

Single nuclei chromatin profiling of ventral midbrain reveals cell identity transcription factors and cell type-specific gene regulatory variation

The paper profiles chromatin accessibility in ventral midbrain single nuclei from two mouse strains, identifies cell types and transcription factors, and finds regulatory variation specific to cell types.

scMM: Mixture-of-experts multimodal deep generative model for single-cell multiomics data analysis.

scMM is a deep generative model that extracts interpretable joint representations and enables cross-modal generation for single-cell multiomics data, improving clustering and data integration.

epiScanpy: integrated single-cell epigenomic analysis

epiScanpy enables analysis of single-cell DNA methylation and ATAC-seq data using scanpy workflows, showing epigenetic markers enrich cell type labels.

Mapping the genetic architecture of human traits to cell types in the kidney identifies mechanisms of disease and potential treatments

The paper maps genetic variants to cell types in the kidney to identify disease mechanisms and drug targets.

The regulatory landscape of cells in the developing mouse cerebellum

This study maps the regulatory landscape of mouse cerebellum development using snATAC-seq, identifying cis-regulatory elements and their spatiotemporal dynamics.