scATAC-seq

Single cell genome and epigenome co-profiling reveals hardwiring and plasticity in breast cancer

The paper introduces wellDA-seq, a method to co-profile genome and epigenome in single cells, revealing genetic hardwiring and epigenetic plasticity in breast cancer.

scConfluence : single-cell diagonal integration with regularized Inverse Optimal Transport on weakly connected features

scConfluence improves single-cell diagonal integration by combining autoencoders with regularized Inverse Optimal Transport, outperforming existing methods in three biological applications.

Single-cell multiome uncovers differences in glycogen metabolism underlying species-specific speed of development

The paper identifies glycogen metabolism differences in pluripotent cells across species that influence neural differentiation speed.

Enhlink infers distal and context-specific enhancer-promoter linkages

Enhlink infers enhancer-promoter linkages using scATAC-seq data and outperforms existing methods, revealing a super-enhancer regulating striatal neuron markers.

Profiling telomere content and composition at single-cell resolution incancer and immune cells

This paper develops a computational framework to quantify telomere content and composition from scATAC-seq data, revealing patient-specific telomere maintenance patterns in cancer and immune cells.

Single-cell analysis of chromatin and expression reveals age- and sex-associated alterations in the human heart

The paper uses single-nucleus ATAC-Seq and RNA-Seq to analyze age and sex differences in human heart cells, identifying gene expression and chromatin changes linked to these factors.

The microbiota affects stem cell decision making in Hydra

The paper shows that Hydra's microbiota influences stem cell decision making, affecting budding capacity through changes in chromatin and transcriptomic landscapes.

Benchmarking computational methods for single-cell chromatin data analysis

The paper benchmarks computational methods for analyzing scATAC-seq data, finding that SnapATAC and SnapATAC2 outperform other methods in cell-type discrimination and scalability.

Single-Molecule Barcoding Technology for Single-Cell Genomics

The paper introduces AmpliDrop, a single-cell genomics barcoding technology that simplifies reagent production and workflow, enabling scalable and flexible experiments.

Comparative single-cell analyses identify shared and divergent features of human and mouse kidney development

The paper compares single-cell chromatin and gene expression data from human and mouse kidney development to identify conserved and divergent features and human-specific enhancer regions linked to kidney disease.

Learning sequence-based regulatory dynamics in single-cell genomics

The paper introduces muBind, a deep learning model that predicts genomic counts from DNA sequences and cell relationships, enhancing understanding of regulatory dynamics during cell transitions.

Single cell multiome profiling of pancreatic islets reveals physiological changes in cell type-specific regulation associated with diabetes risk

The paper uses single-cell multiome profiling to identify gene regulatory changes in pancreatic islets linked to diabetes risk factors like age, sex, and genetic variants.

Integrated Single-Cell Multiomic Profiling of Caudate Nucleus Suggests Key Mechanisms in Alcohol Use Disorder

The paper uses multiomic profiling of the caudate nucleus to identify gene expression and chromatin changes in AUD, linking them to risk genes through QTL analysis.

scaDA: A Novel Statistical Method for Differential Analysis of Single-Cell Chromatin Accessibility Sequencing Data

This paper introduces scaDA, a statistical method for differential chromatin accessibility analysis in scATAC-seq data, showing improved power and FDR control compared to existing methods.

User-friendly exploration of epigenomic data in single cells using sincei

The paper introduces sincei, a command-line toolkit for exploring single-cell epigenomic data from aligned reads, aiming to improve accessibility and flexibility in data analysis.

Enhancer-driven gene regulatory networks inference from single-cell RNA-seq and ATAC-seq data

STREAM infers enhancer-driven gene regulatory networks from single-cell RNA-seq and ATAC-seq data, showing improved performance in TF recovery and enhancer-gene discovery.

Fast clustering and cell-type annotation of scATAC data using pre-trained embeddings

The paper introduces scEmbed, a framework for fast clustering and cell-type annotation of scATAC-seq data using pre-trained embeddings, showing improved performance and transferability.

Controlled Noise: Evidence of Epigenetic Regulation of Single-Cell Expression Variability

This study investigates the link between chromatin accessibility and single-cell expression variability using scATAC-seq and scRNA-seq data from human hematopoietic cells, finding that chromatin accessibility explains much of the variability.

Single-cell epigenomic reconstruction of developmental trajectories in human neural organoid systems from pluripotency

The paper reconstructs epigenomic trajectories in human neural organoids from pluripotency to terminal cell states using single-cell histone modification profiling.

Single-cell multi-omics analysis reveals cooperative transcription factors for gene regulation in oligodendrocytes

The paper identifies cooperative transcription factors in oligodendrocytes using single-cell multi-omics data and validates their regulatory roles through experimental analysis.

Identify Regulatory eQTLs by Multiome Sequencing in Prostate Single Cells

This study uses multiome single-cell sequencing to identify regulatory eQTLs in prostate cancer risk loci, finding overlaps with bulk eQTLs and validating new regulatory SNPs.

A Cell Cycle-aware Network for Data Integration and Label Transferring of Single-cell RNA-seq and ATAC-seq

The paper introduces CCAN, a model that removes cell cycle effects from integrated single-cell multi-omics data while preserving cell type-specific variations, showing strong performance in downstream tasks.

Functional phenotyping of genomic variants using multiomic scDNA-scRNA-seq

This paper introduces SDR-seq, a multiomic scDNA-scRNA-seq method to link genotypes with gene expression, showing variants affect expression in iPSCs and B-cell lymphoma.

Joint tensor modeling of single cell 3D genome and epigenetic data with Muscle

Muscle jointly models single cell 3D genome and DNA methylation data to improve cell type delineation and modality associations.

Liam tackles complex multimodal single-cell data integration challenges

Liam integrates multimodal single-cell data by learning a joint low-dimensional representation, outperforming existing methods on Multiome and CITE-seq datasets.

The Hippo-YAP/TAZ-TEAD axis promotes multipotency in bone marrow stromal cells

This study identifies the Hippo-YAP/TAZ-TEAD axis as a regulator of bone marrow stromal cell multipotency through computational analysis of single-nucleus multiomics data.

Scalable sequence-informed embedding of single-cell ATAC-seq data with CellSpace

CellSpace provides a scalable sequence-informed embedding for scATAC-seq data, capturing cell subpopulations and transcription factor activity while mitigating batch effects.

Single-nucleus RNA/ATAC-seq Reveals SWI/SNF complex activation and allele-specific non-myocyte activation in HCM mouse models

The paper uses single-nucleus RNA/ATAC-seq to analyze HCM mouse models and identifies differences in gene expression and signaling pathways between mutant and wild-type hearts.

Uncovering uncharacterized binding of transcription factors from ATAC-seq footprinting data

This paper introduces DENIS, a framework for de novo motif discovery from ATAC-seq footprints to identify uncharacterized transcription factor binding.

Ploidy inference from single-cell data: application to human and mouse cell atlases

The paper develops a statistical method to infer ploidy from single-cell ATAC-seq data and applies it to human and mouse cell atlases to systematically detect polyploidy across cell types.