FAQ
Is CellKb free?
Users can signup for a free trial license to evaluate CellKb. At the end of the trial, all users need to purchase a license.
Academic and commercial users need to purchase an annual subscription to CellKb to access and download all data.
We also provide paid service options to customize CellKb and integrate it with other databases.
We use PayPal to securely process all payment transactions through the CellKb website. We do not access or store your payment information. We also do not automatically charge your credit card or PayPal account at any time.
We use PayPal to securely process all payment transactions through the CellKb website. We do not access or store your payment information. We also do not automatically charge your credit card or PayPal account at any time.
Contact us to request a demo and pricing.
Note: CellKb Immune is now a part of CellKb.
Who are the developers of CellKb?
CellKb is developed by a small team led by Dr. Ashwini Patil
with technical leadership by Ajay Patil. Ashwini has worked for over 25 years in bioinformatics
research and development. Ajay has more than 30 years of experience in software design and development.
CellKb is licensed through Combinatics Inc., a Japan-based bioinformatics company.
Can I download the marker gene sets in the CellKb database?
Yes. We provide access to the marker gene sets in the CellKb database in machine-readable format through a separate Data License. Please contact us for licensing details.
Users with the Pro and Enterprise licenses can only download the search results obtained from CellKb.
How is the data organized in CellKb?
CellKb is a knowledgebase of cell type specific signatures of gene expression patterns.
It is currently organized into two resources:
1. Cell type signatures from Single-cell RNAseq Datasets
2. Cell type signatures from Bulk RNAseq/microarray Datasets
1. Cell type signatures from Single-cell RNAseq Datasets
2. Cell type signatures from Bulk RNAseq/microarray Datasets
These resources can be searched using a ranked list of genes or a descriptive keyword.
What is a CellKb dataset?
A dataset in a publication contains one or more cell type signatures for a specific condition.
What is a marker gene set or signature in CellKb?
A marker gene set or signature is a cell type specific list of marker genes defined within a dataset.
Each signature is assigned to a cell type.
Marker gene sets for cell types (single-cell clusters) are taken as defined by the authors
in supplementary tables, where available. They are calculated for each cell type using the Wilcoxon rank sum test,
where raw (after normalization) or normalized expression values are available with cell type annotations.
What is a cell type in CellKb?
A cell type is a name given to a signature in a dataset based on its biological
characteristics as described by the authors of the experiment. Signatures with
similar properties are assigned to the same cell type. For example, the cell type
"goblet cell" is associated with multiple signatures from one or more datasets.
Cell types in CellKb are
given appropriate Cell Ontology and/or Uberon Ontology terms where available.
This helps to formalize the cell type nomenclature.
Which species are included in CellKb?
Marker gene sets for 12 species are currently available in CellKb. These are H. sapiens, M. musculus,
D. rerio, C. elegans, D. melanogaster, R. norvegicus, M. fascicularis,
A. thaliana, M. mulatta, O.sativa, G. gorilla and P. troglodytes.
We will continue to add more species as more marker gene sets are published.
How are Cell and/or Uberon Ontology terms assigned to a cell type in CellKb?
Cell and/or Uberon Ontology terms are assigned to cell types and anatomical structures
by manually looking up the most appropriate term(s) based on the biological characteristics
described in the publication. Some cell types may not be assigned a Cell/Uberon Ontology term
if an appropriate term is not found.
How are signatures matching an input list of genes identified in CellKb?
A list of ranked genes can be used to identify matching cell type signatures from single and
bulk datasets, or consensus signtures in CellKb using rank-based method.
This method takes into consideration the number of genes in the user query and cell type signatures,
the number of overlapping genes between the two along with their presence towards the top, middle or
bottom of either list.
How is signature reliability calculated in CellKb?
Signature reliability is calculated as the ratio of the average Spearman's correlation coefficient
of the signature with all other signatures of the same cell type and that with all other cell types.
A value greater than 1 indicates a reliable signature since it is better correlated with other
signatures of the same cell type compared to those of other cell types.
How is the interaction network for query genes calculated in CellKb?
The protein-protein interaction network for query genes is calculated based on experimentally
identified interactions in the HitPredict
database. Gene identifiers given by the user are mapped to protein UniProt IDs and interactions
for these proteins are displayed along with reliability scores calculated by HitPredict. Marker
genes of the matching cell type are highlighted in the network.
How often is CellKb updated?
CellKb is updated 3 times a year - in February, June and October. We are committed to updating CellKb regularly to include the latest publications
identifying cell types using single-cell technologies, add new features, and improve
overall user experience and accessibility.
How do I cite CellKb?
Please reference our website https://www.cellkb.com to cite CellKb.