PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data

By Oscar Franzén, Li-Ming Gan, Johan L. M. Björkegren. Database J. Biol. Databases Curation, 2019

1,362 citations recorded by the source corpus.

Abstract Single-cell RNA sequencing is an increasingly used method to measure gene expression at the single cell level and build cell-type atlases of tissues. Hundreds of single-cell sequencing datasets have already been published. However, studies are frequently deposited as raw data, a format difficult to access for biological researchers due to the need for data processing using complex computational pipelines. We have implemented an online database, PanglaoDB, accessible through a user-friendly interface that can be used to explore published mouse and human single cell RNA sequencing studies. PanglaoDB contains pre-processed and pre-computed analyses from more than 1054 single-cell experiments covering most major single cell platforms and protocols, based on more than 4 million cells from a wide range of tissues and organs. The online interface allows users to query and explore cell types, genetic pathways and regulatory networks. In addition, we have established a community-curated cell-type marker compendium, containing more than 6000 gene-cell-type associations, as a resource for automatic annotation of cell types.

Subfields: Biophysics, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/fa795716fb68ccbe52a8479c4d28da340d932222

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In Biophysics

1. Xia Li

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1. Qin Ma
2. Jacques Colinge
3. Dong Xu
4. Yang Zhang
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Citations in the corpus

• scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses (2021, background): “All of these fi ve targeted genes are marker genes of astrocytes, which have been reported to be associated with AD 47,48 .”
• CellMarker 2.0: an updated database of manually curated cell markers in human/mouse and web tools based on scRNA-seq data (2022, background): “In recent, some databases manually recruit marker genes for different cell types from available literature information, such as PanglaoDB (18), PCMDB (19) and CancerSEA (20).”
• TISCH: a comprehensive web resource enabling interactive single-cell transcriptome visualization of tumor microenvironment (2020, background): “There have been efforts to systematically collect and curate single-cell datasets, such as CancerSEA, scRNASeqDB, SCPortalen, PanglaoDB, and JingleBells (9-13).”
• A comparison of automatic cell identification methods for single-cell RNA sequencing data (2019, background): “Moreover, public databases of cell type markers (e.g., PanglaoDB [39] and CellMarker [40]) often provide different markers for the same population.”
• SingleCellSignalR: inference of intercellular networks from single-cell transcriptomics (2019, background): “Cell-type calling is implemented based on a list of gene signatures following a format identical to PanglaoDB (37) exports such that users can easily add cell types from this rich source or provide their own.”