scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells
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 col...
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doaj-ce08891709ae42818c1985c689b649f02020-11-24T20:45:32ZengMDPI AGGenes2073-44252017-12-0181236810.3390/genes8120368genes8120368scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single CellsYuan Cao0Junjie Zhu1Peilin Jia2Zhongming Zhao3Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USADepartment of Electrical Engineering, Stanford University, Stanford, CA 94305, USACenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USACenter for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USASingle-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/.https://www.mdpi.com/2073-4425/8/12/368single cellRNA sequencingdatabaseexpression profilecell typedifferential expression |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yuan Cao Junjie Zhu Peilin Jia Zhongming Zhao |
spellingShingle |
Yuan Cao Junjie Zhu Peilin Jia Zhongming Zhao scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells Genes single cell RNA sequencing database expression profile cell type differential expression |
author_facet |
Yuan Cao Junjie Zhu Peilin Jia Zhongming Zhao |
author_sort |
Yuan Cao |
title |
scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells |
title_short |
scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells |
title_full |
scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells |
title_fullStr |
scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells |
title_full_unstemmed |
scRNASeqDB: A Database for RNA-Seq Based Gene Expression Profiles in Human Single Cells |
title_sort |
scrnaseqdb: a database for rna-seq based gene expression profiles in human single cells |
publisher |
MDPI AG |
series |
Genes |
issn |
2073-4425 |
publishDate |
2017-12-01 |
description |
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/. |
topic |
single cell RNA sequencing database expression profile cell type differential expression |
url |
https://www.mdpi.com/2073-4425/8/12/368 |
work_keys_str_mv |
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