ArticleFrontiers in genetics2019
SCDevDB: A Database for Insights Into Single-Cell Gene Expression Profiles During Human Developmental Processes.
Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 12 papers.
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Who cites it
12 citing papers in PubMed.
- Immune regulation and therapeutic targets in sepsis: insights from single-cell transcriptomics.Frontiers in immunology · 2026Review
- A statistical approach for systematic identification of transition cells from scRNA-seq data.Cell reports methods · 2024Article
- NTCdb: Single-cell transcriptome database of human inflammatory-associated diseases.Computational and structural biotechnology journal · 2024Article
- A Systematic Overview of Single-Cell Transcriptomics Databases, their Use cases, and Limitations.ArXiv · 2024Article
- A systematic overview of single-cell transcriptomics databases, their use cases, and limitations.Frontiers in bioinformatics · 2024Review
- Review
- ABC portal: a single-cell database and web server for blood cells.Nucleic acids research · 2023Article
- A paediatric dysembryoplastic neuroepithelial tumour (DNET) with deregulated stem cell markers: a case report.Translational pediatrics · 2022Article
- Article
- SC2disease: a manually curated database of single-cell transcriptome for human diseases.Nucleic acids research · 2021Article
- Genome-Wide Association Studies Reveal Neurological Genes for Dog Herding, Predation, Temperament, and Trainability Traits.Frontiers in veterinary science · 2021Article
- MyoData: An expression knowledgebase at single cell/nucleus level for the discovery of coding-noncoding RNA functional interactions in skeletal muscle.Computational and structural biotechnology journal · 2021Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Single-cell RNA-seq studies profile thousands of cells in developmental processes. Current databases for human single-cell expression atlas only provide search and visualize functions for a selected gene in specific cell types or subpopulations. These databases are limited to technical properties or visualization of single-cell RNA-seq data without considering the biological relations of their collected cell groups. Here, we developed a database to investigate single-cell gene expression profiling during different developmental pathways (SCDevDB). In this database, we collected 10 human single-cell RNA-seq datasets, split these datasets into 176 developmental cell groups, and constructed 24 different developmental pathways. SCDevDB allows users to search the expression profiles of the interested genes across different developmental pathways. It also provides lists of differentially expressed genes during each developmental pathway, T-distributed stochastic neighbor embedding maps showing the relationships between developmental stages based on these differentially expressed genes, Gene Ontology, and Kyoto Encyclopedia of Genes and Genomes analysis results of these differentially expressed genes. This database is freely available at https://scdevdb.deepomics.org.
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