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Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. Here, we present scmap, a method (source available at https://github.com/hemberg-lab/scmap and the application can be run from http://www.hemberg-lab.cloud/scmap) for projecting cells from a scRNA-seq experiment on to the cell-types identified in a different experiment.

A Cloud implementation of scmap can be used for free without any restriction here. Instructions on how to set it up on your own Cloud are available here.

Q: How to install/run scmap?
A: Please follow instruction on Bioconductor page. If there are any problems you can install scmap from GitHub:

# run this in your R session
install.packages("devtools")
devtools::install_github("hemberg-lab/scmap")

Q: Where can I report bugs, comments, issues or suggestions?
A: Please use this page.

Q: Where can I ask questions about scmap?
A: Please use this page.

Q: Is scmap published?
A: Yes, it is published in Nature Methods.

Q: What is scmap licence?
A: GPL-3