SCDevDB : A Database for Insights Into Single-Cell Gene Expression Profiles During Human Developmental Processes
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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Detail(s)
Original language | English |
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Article number | 903 |
Journal / Publication | Frontiers in Genetics |
Volume | 10 |
Online published | 26 Sept 2019 |
Publication status | Published - Sept 2019 |
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DOI | DOI |
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Attachment(s) | Documents
Publisher's Copyright Statement
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Link to Scopus | https://www.scopus.com/record/display.uri?eid=2-s2.0-85073153774&origin=recordpage |
Permanent Link | https://scholars.cityu.edu.hk/en/publications/publication(18d6ad0a-0999-4eab-b008-d2fdfc2ae6f4).html |
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
Research Area(s)
- single cell, gene expression, development, database, cell type, differential expression, STEM-CELLS, MUSCLE, MYL2, TRANSCRIPTOME, MUTATIONS, BIOLOGY, EMBRYOS, LINES
Citation Format(s)
SCDevDB: A Database for Insights Into Single-Cell Gene Expression Profiles During Human Developmental Processes. / Wang, Zishuai; Feng, Xikang; Li, Shuai Cheng.
In: Frontiers in Genetics, Vol. 10, 903, 09.2019.
In: Frontiers in Genetics, Vol. 10, 903, 09.2019.
Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal › peer-review
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