Database Commons
Database Commons

a catalog of worldwide biological databases

Database Profile

PanglaoDB

General information

URL: https://panglaodb.se/
Full name:
Description: PanglaoDB is a database for the scientific community interested in exploration of single cell RNA sequencing experiments from mouse and human. We collect and integrate data from multiple studies and present them through a unified framework.
Year founded: 2019
Last update: 2020-05-21
Version:
Accessibility:
Manual:
Accessible
Country/Region: Sweden

Classification & Tag

Data type:
RNA
Data object:
Database category:
Major species:
Keywords:

Contact information

University/Institution: Karolinska Institute
Address: Integrated Cardio Metabolic Centre (ICMC), Department of Medicine, Karolinska Institutet, Novum SE Huddinge, Sweden
City:
Province/State:
Country/Region: Sweden
Contact name (PI/Team): Oscar Franzén
Contact email (PI/Helpdesk): contact@panglaodb.se

Publications

30951143
PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data. [PMID: 30951143]
Franzén O, Gan LM, Björkegren JLM.

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.

Database (Oxford). 2019:2019() | 553 Citations (from Europe PMC, 2024-11-30)

Ranking

All databases:
127/6265 (97.989%)
Expression:
21/1209 (98.346%)
127
Total Rank
491
Citations
98.2
z-index

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Record metadata

Created on: 2019-11-27
Curated by:
Xinyu Zhou [2023-10-08]
Yuxin Qin [2023-09-19]
Dong Zou [2019-11-27]