scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells

被引:68
|
作者
Cao, Yuan [1 ]
Zhu, Junjie [2 ]
Jia, Peilin [1 ]
Zhao, Zhongming [1 ,3 ,4 ]
机构
[1] Univ Texas Hlth Sci Ctr Houston, Ctr Precis Hlth, Sch Biomed Informat, Houston, TX 77030 USA
[2] Stanford Univ, Dept Elect Engn, Stanford, CA 94305 USA
[3] Univ Texas Hlth Sci Ctr Houston, Sch Publ Hlth, Human Genet Ctr, Houston, TX 77030 USA
[4] Vanderbilt Univ, Dept Biomed Informat, Med Ctr, Nashville, TN 37203 USA
基金
中国国家自然科学基金; 美国国家卫生研究院;
关键词
single cell; RNA sequencing; database; expression profile; cell type; differential expression; PROGENITOR; STEM; TOOL;
D O I
10.3390/genes8120368
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
Single-cell RNA sequencing (scRNA-Seq) is rapidly becoming a powerful tool for high-throughput transcriptomic analysis of cell states and dynamics at the single cell level. Both the number and quality of scRNA-Seq datasets have dramatically increased recently. A database that can comprehensively collect, curate, and compare expression features of scRNA-Seq data in humans has not yet been built. Here, we present scRNASeqDB, a database that includes almost all the currently available human single cell transcriptome datasets (n = 38) covering 200 human cell lines or cell types and 13,440 samples. Our online web interface allows users to rank the expression profiles of the genes of interest across different cell types. It also provides tools to query and visualize data, including Gene Ontology and pathway annotations for differentially expressed genes between cell types or groups. The scRNASeqDB is a useful resource for single cell transcriptional studies. This database is publicly available at https://bioinfo.uth.edu/scrnaseqdb/.
引用
收藏
页数:10
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