Single-cell chromatin accessibility sequencing (scCAS) has emerged as a valuable tool for interrogating and elucidating epigenomic heterogeneity gene regulation. However, scCAS data inherently suffers from limitations such high sparsity dimensionality, which pose significant challenges downstream analyses. Although several methods are proposed to enhance data, there still that hinder the effectiveness of these methods. Here, we propose scCASE, enhancement method based on non-negative matrix...

Gene regulatory elements, including promoters, enhancers, silencers, etc., control transcriptional programs in a spatiotemporal manner. Though these elements are known to be able induce either positive or negative control, the community has been mostly studying enhancers which amplify transcription initiation, with less emphasis given silencers repress gene expression. To facilitate study of and investigation their potential roles we developed SilencerDB...

<title>Abstract</title> Large-scale foundation models have recently opened a new avenue to artificial general intelligence for life sciences, showing great promise in the analysis of single-cell transcriptomic data. Nevertheless, such challenges as tremendous number signaling regions, extreme data sparsity, and nearly binary nature epigenomic prevented construction model epigenomics thus far, though it is evident that abundant properties chromatin accessibility provide more decisive insights...

Recent advances in spatial epigenomic techniques have given rise to assay for transposase-accessible chromatin using sequencing (spATAC-seq) data, enabling the characterization of heterogeneity and information simultaneously. Integrative analysis multiple spATAC-seq samples, which no method has been developed, allows effective identification elimination unwanted non-biological factors within comprehensive exploration tissue structures providing a holistic landscape, thereby facilitating...

Abstract Chromatin accessibility, as a powerful marker of active DNA regulatory elements, provides valuable information for understanding mechanisms. The revolution in high-throughput methods has accumulated massive chromatin accessibility profiles public repositories. Nevertheless, utilization these data is hampered by cumbersome collection, time-consuming processing, and manual (openness) annotation genomic regions. To fill this gap, we developed OpenAnnotate...

Abstract Spatially resolved sequencing technologies have revolutionized the characterization of biological regulatory processes within microenvironment by simultaneously accessing states genomic regions, genes and proteins, along with spatial coordinates cells, necessitating advanced computational methods for cross-modality multi-sample integrated analysis omics datasets. To address this gap, we propose PRESENT, an effective scalable contrastive learning framework, representation spatially...

ABSTRACT Chromatin accessibility, as a powerful marker of active DNA regulatory elements, provides valuable information for understanding mechanisms. The revolution in high-throughput methods has accumulated massive chromatin accessibility profiles public repositories. Nevertheless, utilization these data is hampered by cumbersome collection, time-consuming processing, and manual (openness) annotation genomic regions. To fill this gap, we developed OpenAnnotate (...

Abstract Single-cell sequencing technology has enabled the characterization of cellular heterogeneity at an unprecedented resolution. To analyze single-cell RNA-sequencing data, numerous tools have been proposed for various analytic tasks, which systematically summarized and concluded in a comprehensive database called scRNA-tools. Although epigenomic data can effectively reveal chromatin regulatory landscape that governs transcription, analysis presents assay-specific challenges, abundance...

Abstract Summary Cell-cell communication through ligand-receptor pairs forms the cornerstone for complex functionalities in multicellular organisms. Deciphering such intercellular signaling can contribute to un-raveling disease mechanisms and enables targeted therapy. Nonetheless, notable biases inconsistencies are evident among inferential outcomes generated by current methods inferring cell-cell network. To fill this gap, we developed collectNET ( http://health.tsing-hua.edu.cn/collectnet...

Abstract Cell–cell communication (CCC) through ligand–receptor (L–R) pairs forms the cornerstone for complex functionalities in multicellular organisms. Deciphering such intercellular signaling can contribute to unraveling disease mechanisms and enable targeted therapy. Nonetheless, notable biases inconsistencies are evident among inferential outcomes generated by current methods inferring CCC network. To fill this gap, we developed collectNET (http://health.tsinghua.edu.cn/collectnet) as a...

Spatial epigenomic technologies enable simultaneous capture of spatial location and chromatin accessibility cells within tissue slices. Identifying peaks that display variation cellular heterogeneity is the key analytic task for characterizing landscape complex tissues. Here, we propose an efficient iterative model, Descart, spatially variable identification based on graph inter-cellular correlations. Through comprehensive benchmarking, demonstrate superiority Descart in revealing capturing...

Abstract Recent advances in spatial epigenomic techniques have given rise to assay for transposase-accessible chromatin using sequencing (spATAC-seq) data, enabling the characterization of heterogeneity and information simultaneously. Integrative analysis multiple spATAC-seq samples, which no method has been developed, allows effective identification elimination unwanted non-biological factors within comprehensive exploration tissue structures providing a holistic landscape, thereby...

Identifying cis-regulatory elements (CREs) within non-coding genomic regions-such as enhancers, silencers, promoters, and insulators-is pivotal for elucidating the intricate gene regulatory mechanisms underlying complex biological traits. The current prevalent sequence-based methods often focus on singular CRE types, limiting insights into cell-type-specific implications. Here, we introduce CREATE, a multimodal deep learning model based Vector Quantized Variational AutoEncoder framework,...

Large-scale foundation models have recently opened new avenues for artificial general intelligence. Such a research paradigm has shown considerable promise in the analysis of single-cell sequencing data, while to date, efforts centered on transcriptome. In contrast gene expression, chromatin accessibility provides more decisive insights into cell states, shaping regulatory landscapes that control transcription distinct types. Yet, challenges also persist due abundance features, high data...

Abstract The change of CH4 oxidation cause by adding C7H16 from small to large scale temperature at high pressures were precisely examined under laboratory condition with the temperatures span 400K 1200K and are regulated 1atm 10atm a reaction container equivalence ratio 0.5. proportion in CH4/C7H16 mixed substances was varies zero one hundred percent. molar ratios for CH4, C7H16, O2, CO, CO2, formaldehyde, ethene investigated during several trial runs, mechanism is selected establish...