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The accuracy of spatial gene expression profiles generated by probe-based in situ spatially resolved transcriptomic technologies depends on the specificity with which probes bind to their intended target gene. Off-target binding, defined as a probe …
Read PDFPrevious studies on the characterization of regulatory T cells (Tregs) in the thymus have proven to be simplistic. Here, we present a protocol for identifying recirculating thymic Tregs in mice and characterizing the role of …
Read PDF<h4>Background</h4>Head and neck squamous cell carcinoma (HNSC) exhibits substantial prognostic and microenvironmental heterogeneity. However, the integrated prognostic relevance of synergistic immune and inflammatory signatures in HNSC remains fully elucidated.<h4>Methods</h4>Weighted gene coexpression network analysis (WGCNA) was …
Read PDFThe Chicken Genotype-Tissue Expression (ChickenGTEx) project was established to systematically characterize the regulatory landscape of the chicken genome and to accelerate the translation of functional genomics into precision breeding. By integrating whole-genome sequencing with multi-tissue …
Read PDFSingle-nuclei RNA sequencing enables the interrogation of tissue microenvironments in clinical samples preserved by snap-freezing, where cell membrane damage precludes single-cell isolation, but nuclei remain intact for high-quality molecular profiling. Here, we present an optimized …
Read PDFThe aggressive clinical course and limited treatment avenues for key bone malignancies, specifically osteosarcoma, Ewing's sarcoma, and giant cell tumor of bone, are heavily dictated by their intricate tumor microenvironment (TME). To decode this cellular …
Read PDF<h4>Motivation</h4>Clustering single-cell RNA sequencing (scRNA-seq) data plays a vital role in the study of cellular heterogeneity. Many algorithms have been developed to cluster scRNA-seq data. However, traditional clustering algorithms often fail to capture local consistency, …
Read PDF<h4>Motivation</h4>Understanding temporal gene expression is fundamental in the study of cellular development and differentiation. In practice, temporal single-cell datasets tend to contain only a limited number of measured time points, which are often unevenly spaced, …
Read PDF<h4>Motivation</h4>Single-cell RNA sequencing (scRNA-seq) data analysis is often performed using network projections that produce co-expression networks. These network-based algorithms are attractive because regulatory interactions are fundamentally network-based and there are many tools available for downstream …
Read PDF<h4>Summary</h4>Reconstructing gene regulatory networks (GRNs) from single-cell RNA sequencing (scRNA-seq) data is fundamental for understanding cellular dynamics at the molecular level but requires sophisticated workflows. Here, we introduce CellCraft, a web-based application designed to streamline …
Read PDF<h4>Motivation</h4>Commercial solutions like 10X cellranger provide robust UMI quantification for their proprietary single-cell protocols, but open methods such as Smart-seq3 lack comparable support.<h4>Results</h4>Here, we introduce umite, a Smart-seq3 UMI counting pipeline with a focus on …
Read PDFThe increasing scale and complexity of proteomics data demand robust, scalable, and interpretable quality control (QC) frameworks to ensure data reliability and reproducibility. Here, we present pmultiqc, an open-source Python package that standardizes and generates …
Read PDF<h4>Summary</h4>CatsCradle is an R package for single-cell analysis that exploits the duality between cells and the genes they express. Our package provides tools to cluster genes, visualize relationships between them, and to explore relationships between …
Read PDF<h4>Motivation</h4>Heterogeneity is a hallmark of both macroscopic complex diseases and microscopic single-cell distribution. Gaussian graphical models (GGMs)-based heterogeneity analysis highlights its important role in capturing the essential characteristics of biological regulatory networks, but faces instability …
Read PDFBACKGROUND Retinopathy of prematurity is characterized by retinal vascular ischemia and hypoxia that lead to neovascularization, potentially causing retinal detachment and blindness. This study aimed to explore target genes involved in oxygen-induced retinopathy (OIR) through …
Read PDF<h4>Motivation</h4>Spatial transcriptome data have both gene expression information and cell spatial location information, offering exceptional prospects for analyzing cell-cell interaction (CCI) network. Most existing statistical and optimal transport-based methods rely only on known ligand-receptor pairs …
Read PDF<h4>Motivation</h4>Large-scale omics resources, including The Cancer Genome Atlas, Genomics of Drug Sensitivity in Cancer, and the Cancer Dependency Map, have become essential for cancer research. However, these datasets are distributed across different platforms, formats and …
Read PDFSingle-cell allele-specific expression (ASE) provides valuable insights into gene regulatory mechanisms. However, its utility is limited by the lack of dedicated computational tools. We present DAESC + , a dual-module end-to-end software package for the …
Read PDF<h4>Motivation</h4>Cell annotation is fundamental for single-cell data interpretation. Accurate annotation allows us to identify cell types, understand their functions, trace developmental trajectories, and pinpoint alterations associated with a condition of interest. However, this complex process …
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