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.

Usage examples
Oscar Franzén, Li-Ming Gan, Johan L M Björkegren, PanglaoDB: a web server for exploration of mouse and human single-cell RNA sequencing data, Database, Volume 2019, 2019, baz046,
What is single cell RNA sequencing?

Adapted from the Wikipedia article on the topic: Single cell RNA sequencing examines the transcriptomes from individual cells with optimized next generation sequencing technologies, providing a higher resolution of gene expression and a better understanding of the function of an individual cell in the context of its microenvironment.

Database statistics
Mus musculus Homo sapiens
Samples 925258
Tissues 160 64
Cells 3,797,863989,842
Clusters 8,6511,748
Dataset of the day
Take a closer look at the cellular composition of Muscle, using a dataset which consists of 290 cells. Clustering of this dataset resulted in 3 cell clusters, containing among others, Neutrophils.
12-04-2019 We are happy to announce alona - a cloud-based single cell analysis service! Try it out.
02-04-2019 Metadata can be downloaded from our github repo.
Show older news
26-03-2019 The marker download link ("get tsv file") is now a stable link. It can be linked directly in scripts.
19-03-2019 Our manuscript entitled "PanglaoDB: A Web Server for Exploration of Mouse and Human Single Cell RNA Sequencing Data" has been accepted in the journal Database.
18-03-2019 Markers can be voted for. In an experiment to try to extract crowd-enabled wisdom, we have introduced a voting function for markers. Markers can be upvoted or downvoted using small arrows on the marker page. Each visitor has one vote per marker-cell type. An anonymous hash is computed to store voting status. Arrows become visible when selecting a specific cell type from the list. Voting does not require registration, and it is done anonymously.
19-11-2018 Differential expression analysis now takes input threshold arguments (q-value and log fold change).
16-11-2018 Differential expression analysis is now available. Enter the interactive view for a sample, then click the "Differential expression" link.