ArticleBMC bioinformatics2021
Asc-Seurat: analytical single-cell Seurat-based web application.
Article in BMC bioinformatics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
45 citing papers in PubMed.
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- Ferroptosis-Based Peripheral Immune Dysregulation and Diagnostic Signatures in Parkinson's Disease: An RNA Transcriptomic and Single-Cell Immune Sequencing Analysis.FASEB journal : official publication of the Federation of American Societies for Experimental Biology · 2026Article
- Identification and Experimental Validation of Key Genes Related to Neuroendocrine in Periodontitis Based on Single-Cell and Bulk Transcriptome Data.Journal of cellular and molecular medicine · 2026Article
- Integrating single-cell RNA sequencing with multi-omics to decode disease microenvironments.Molecular biology reports · 2026Review
- Tenascin C promotes the formation of abdominal aortic aneurysm by regulating the homeostasis of vascular smooth muscle cells.Biology direct · 2026Article
- The Gene Ontology knowledgebase in 2026.Nucleic acids research · 2026Article
- Investigating the causal impact of gut microbiota on periodontitis based on Mendelian randomization, bulk transcriptomics, and single-cell transcriptomics.Frontiers in cell and developmental biology · 2026Article
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- ScRDAVis: An R shiny application for single-cell transcriptome data analysis and visualization.PLoS computational biology · 2025Article
- The impact of PANoptosis-related genes on immune profiles and subtype classification in ischemic stroke.Scientific reports · 2025Article
- Single-nucleus transcriptomics revealed auxin-driven mechanisms of wood plasticity to enhance severe drought tolerance in poplar.Genome biology · 2025Article
- Analysis of Microarray and Single-Cell RNA-Seq Finds Gene Co-Expression and Tumor Environment Associated with Extracellular Matrix in Epithelial-Mesenchymal Transition in Prostate Cancer.International journal of molecular sciences · 2025Article
- Deep tissue profiling of Populus stem at single nucleus level reveals uncharacterized cell types and cell-specific gene regulatory networks.Genome biology · 2025Article
- CytoAnalyst web platform facilitates comprehensive single cell RNA sequencing analysis.Scientific reports · 2025Article
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- Navigating single-cell RNA-sequencing: protocols, tools, databases, and applications.Genomics & informatics · 2025Review
- Investigating biological nitrogen fixation via single-cell transcriptomics.Journal of experimental botany · 2025Review
- Analysis of microarray and single-cell RNA-seq identifies gene co-expression, cell-cell communication, and tumor environment associated with metabolite interconversion enzyme in prostate cancer.Discover oncology · 2025Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundSingle-cell RNA sequencing (scRNA-seq) has revolutionized the study of transcriptomes, arising as a powerful tool for discovering and characterizing cell types and their developmental trajectories. However, scRNA-seq analysis is complex, requiring a continuous, iterative process to refine the data and uncover relevant biological information. A diversity of tools has been developed to address the multiple aspects of scRNA-seq data analysis. However, an easy-to-use web application capable of conducting all critical steps of scRNA-seq data analysis is still lacking. We present Asc-Seurat, a feature-rich workbench, providing an user-friendly and easy-to-install web application encapsulating tools for an all-encompassing and fluid scRNA-seq data analysis. Asc-Seurat implements functions from the Seurat package for quality control, clustering, and genes differential expression. In addition, Asc-Seurat provides a pseudotime module containing dozens of models for the trajectory inference and a functional annotation module that allows recovering gene annotation and detecting gene ontology enriched terms. We showcase Asc-Seurat's capabilities by analyzing a peripheral blood mononuclear cell dataset.
conclusionsAsc-Seurat is a comprehensive workbench providing an accessible graphical interface for scRNA-seq analysis by biologists. Asc-Seurat significantly reduces the time and effort required to analyze and interpret the information in scRNA-seq datasets.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.