scATAC-seq

scMomer: A modality-aware pretraining framework for single-cell multi-omics modeling under missing modality conditions

scMomer is a pretraining framework for single-cell multi-omics modeling under missing modality conditions, generating biologically meaningful embeddings and outperforming unimodal approaches in downstream tasks.

Spatial multi-omics defines a shared infiltrative signature in glioblastoma at the resection margin

This study identifies a shared infiltrative signature in glioblastoma at the resection margin using spatial multi-omics data and validates EGFR as a key marker.

Epiregulon: Inference of single-cell transcription factor activity to predict drug response and drivers of cell state

Epiregulon infers single-cell TF activity using ATAC-seq and RNA-seq to predict drug response and identify drivers of cell state.

Single-cell multiomics reveals the oscillatory dynamics of mRNA metabolism and chromatin accessibility during the cell cycle

The paper uses single-cell multiomics to analyze mRNA metabolism and chromatin accessibility dynamics during the cell cycle, revealing oscillatory patterns and regulatory mechanisms.

Cross-species Multimodal Single-cell Profiling of Dorsal and Ventral Prefrontal Cortex Reveals Cell-type Divergence and PTSD-associated Regulatory Landscapes

The paper integrates multi-omic data from mouse and human prefrontal cortex subregions to identify cell-type-specific PTSD risk factors and regulatory landscapes.

snATAC-Express infers Gene Expression from Prioritized Chromatin Accessibility Peaks using Machine Learning

The paper develops a machine learning pipeline to infer gene expression from chromatin accessibility peaks using single nuclear multi-omic data, finding that important peaks are enriched in GWAS variants for inflammatory bowel disease and lupus.

Dual role of ZIC2 during neural induction: from pioneer transcription factor to enhancer activator

This study investigates ZIC2's role in neural development, showing it acts as a pioneer transcription factor during pluripotency exit and an enhancer activator during neural induction.

Comparative single-cell lineage bias in human and murine hematopoietic stem cells

The paper investigates lineage commitment bias in human and murine hematopoietic stem cells, finding that variation in myeloid and lymphoid engraftment is stochastic and not due to cell-intrinsic bias.

Quality control of single-cell ATAC-seq data without peak calling using Chromap

This paper extends Chromap to provide peak-based quality control metrics for single-cell ATAC-seq without peak calling, improving downstream analysis by identifying low-quality cells missed by other methods.

sCIN: A Contrastive Learning Framework for Single-Cell Multi-omics Data Integration

sCIN integrates single-cell multi-omics data using contrastive learning, outperforming existing methods on paired and unpaired datasets.

scAGCI: an anchor graph-based method for cell clustering from integrated scRNA-seq and scATAC-seq data

scAGCI improves cell clustering in integrated scRNA-seq and scATAC-seq data by using anchor graphs to capture shared and specific information, achieving better performance and biological relevance.

Facilitate integrated analysis of single cell multiomic data by binarizing gene expression values

This paper shows that binarizing scRNA-seq data and integrating it with scATAC-seq data using TF-IDF and LSI improves clustering for multiomic analysis.

Decoding DNA sequence-driven evolution of the human brain epigenome at cellular resolution

The paper identifies evolutionary patterns in the human brain epigenome using single-cell ATAC-seq data, revealing lineage-specific regulatory changes and their association with brain disease variants.

Integrated single-cell multiome analysis reveals muscle fiber-type gene regulatory circuitry modulated by endurance exercise

The paper uses single-nucleus multiome sequencing to analyze gene regulatory changes in human skeletal muscle after endurance exercise, identifying fiber-type specific regulatory programs and transcription factor networks.

ScReNI: single-cell regulatory network inference through integrating scRNA-seq and scATAC-seq data

ScReNI integrates scRNA-seq and scATAC-seq data to infer cell-specific regulatory networks and identify cell-enriched regulators.

Alevin-fry-atac enables rapid and memory frugal mapping of single-cell ATAC-seq data using virtual colors for accurate genomic pseudoalignment

Alevin-fry-atac provides a fast, memory-efficient method for single-cell ATAC-seq data processing with high accuracy compared to existing tools.

Deciphering gene regulatory programs in mouse embryonic skin through single-cell multiomics analysis

The paper uses single-cell multiomics to study gene regulatory programs in mouse embryonic skin, identifying cis-regulatory elements and transcription factors involved in development.

Single cell functional immunogenomics of the fallopian tube reveals a precursor immune surveillance network for ovarian cancer prevention

The paper uses single-cell sequencing to show that immune cells in the fallopian tube share clonotypes with ovarian cancer tumors, suggesting a role in early immune surveillance.

Restriction of innate Tγδ17 cell plasticity by an AP-1 regulatory axis

This study identifies an AP-1 regulatory axis that restricts Tγδ17 cell plasticity by stabilizing type 3 identity and preventing conversion to type 1 effectors during infection.

MitoTracer facilitates the identification of informative mitochondrial mutations for precise lineage reconstruction

MitoTracer identifies informative mitochondrial mutations for lineage reconstruction from scRNA-seq and scATAC-seq data, showing high sensitivity and specificity.

Quantitative measurement of phenotype dynamics during cancer drug resistance evolution using genetic barcoding

This paper develops a mathematical framework to infer cancer drug resistance dynamics from genetic lineage tracing and population size data, validated using experimental evolution and single-cell sequencing.

Multimodal single-cell analyses reveal distinct fusion-regulated transcriptional programs in Ewing sarcoma.

The paper identifies distinct transcriptional programs in Ewing sarcoma driven by EWS::FLI1 fusions and shows their variability across tumors and cell lines.

Vaccines combining slow delivery and follicle targeting of antigens increase germinal center B cell clonal diversity and clonal expansion

This study shows that combining slow antigen delivery and follicle-targeting adjuvants enhances germinal center B cell diversity and clonal expansion in mice.

Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance

The paper introduces pgBoost, a framework that improves linking regulatory variants to genes by integrating single-cell multiome data and genomic distance, showing higher enrichment than existing methods.

Pioneer factor ETV2 safeguards endothelial cell specification by recruiting the repressor REST to restrict alternative lineage commitment

This study identifies ETV2's role in endothelial cell specification by recruiting REST to repress alternative lineage genes through single-cell RNA-seq and ATAC-seq analyses.

Single Nucleotide Polymorphism (SNP) and Antibody-based Cell Sorting (SNACS): A tool for demultiplexing single-cell DNA sequencing data

The paper introduces SNACS, a method for demultiplexing single-cell DNA sequencing data using SNPs and cell-surface antibodies, achieving higher accuracy than existing methods.

Decoding gene regulatory networks controlling hypothalamic and prethalamic development.

This study identifies gene regulatory networks controlling hypothalamic and prethalamic development using single-cell RNA and ATAC sequencing in mice, revealing key transcription factors and their roles in metabolic and cognitive traits.

Cell-type-specific patterns and consequences of somatic mutation in development and aging brain

The paper introduces Duplex-Multiome, a method to identify cell-type-specific somatic mutations in brain tissue, revealing age-related mutation patterns and developmental lineage relationships.

A Temporal Single-Cell Multi-Omics Atlas of Murine Pancreatic Islet Remodeling During Hyperglycaemia Progression

This study maps dynamic changes in murine pancreatic islet cell composition and transcriptional states during hyperglycaemia progression using single-cell multi-omics data.

scMODAL: A general deep learning framework for comprehensive single-cell multi-omics data alignment with feature links

scMODAL is a deep learning framework for aligning single-cell multi-omics data using feature links, effectively removing unwanted variation and identifying cell subpopulations.