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Genes 2017, 8(12), 368; doi:10.3390/genes8120368

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

1,†
,
2,†
,
1
and
1,3,4,*
1
Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
2
Department of Electrical Engineering, Stanford University, Stanford, CA 94305, USA
3
Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
4
Department of Biomedical Informatics, Vanderbilt University Medical Center, Nashville, TN 37203, USA
These authors contributed equally to this work.
*
Author to whom correspondence should be addressed.
Received: 13 November 2017 / Revised: 30 November 2017 / Accepted: 30 November 2017 / Published: 5 December 2017
(This article belongs to the Special Issue Integrative Genomics and Systems Medicine in Cancer)
View Full-Text   |   Download PDF [2777 KB, uploaded 5 December 2017]   |  

Abstract

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 bioinfo.uth.edu/scrnaseqdb/. View Full-Text
Keywords: single cell; RNA sequencing; database; expression profile; cell type; differential expression single cell; RNA sequencing; database; expression profile; cell type; differential expression
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Cao, Y.; Zhu, J.; Jia, P.; Zhao, Z. scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells. Genes 2017, 8, 368.

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