4.6 Article

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

期刊

GENES
卷 8, 期 12, 页码 -

出版社

MDPI
DOI: 10.3390/genes8120368

关键词

single cell; RNA sequencing; database; expression profile; cell type; differential expression

资金

  1. National Institutes of Health [R01LM012806, R01LM011177]
  2. China Scholarship Council
  3. National Natural Science Foundation of China [81572620]
  4. Shandong Provincial Natural Science Foundation of China [ZR2015HM003]

向作者/读者索取更多资源

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/.

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