<img src=inst/scmap.png height="200">
## scmap - A tool for unsupervised projection of single cell RNA-seq data
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.
## Cloud-based scmap
A Cloud implementation of __scmap__ can be used for free without any restriction [here](http://www.hemberg-lab.cloud/scmap). Instructions on how to set it up on your own Cloud are available [here](https://github.com/hemberg-lab/scmap-shiny).
__Q__: How to install/run __scmap__?
__A__: Please follow instruction on [Bioconductor page](http://bioconductor.org/packages/scmap). If there are any problems you can install __scmap__ from GitHub:
# run this in your R session
__Q__: Where can I report bugs, comments, issues or suggestions?
__A__: Please use [this page](https://github.com/hemberg-lab/scmap/issues).
__Q__: Where can I ask questions about __scmap__?
__A__: Please use [this page](https://support.bioconductor.org/p/new/post/?tag_val=scmap).
__Q__: Is __scmap__ published?
__A__: Yes, it is published in [Nature Methods](https://www.nature.com/articles/nmeth.4644).
__Q__: What is __scmap__ licence?