How it works
OpenCyto allows users to perform data driven automated gating of cytometry data in BioConductor. Users build a gating template that defines a hierarchical relationship between cell populations, the parameters used to define them, and a series of data-driven gating algorithms to use.
Gates are not created until the algorithms actually see some data.
When the template is applied to a data set, openCyto then instantiates gates for each sample and cell population in a data-driven manner.
OpenCyto Docker Image
An openCyto docker image is available for easy installation.
At the command line install the image.:
> docker pull gfinak/opencyto
docker run gfinak/opencyto
Then navigate to
localhost:8787 in your browser (
Compatible Bioconductor Data structures
OpenCyto acts on Bioconductor objects called
GatingSet is a collection of
GatingHierarchy is a data structure holding data from a single FCS file (as a
flowFrame) together with its associated metadata, annotations, cell populations, gates, etc.
A GatingSet can also be constructed from a flowSet object using the
The GatingSet will have no associated gates or populations, but these can be added using
add_pop() from openCyto.
openCyto and the underlying core cytometry infrastructure has enabled a number of different projects:
- COMPASS: Combinatorial polyfunctionality analysis of single cells
- ggcyto: use the grammar of graphics to visualize cytometry data
- CytoML: Convert gated cytometry data between platforms
- flowWorkspace Introduction: A Package to store and maninpulate gated flow data
- How to merge GatingSets
- How to plot gated data this is superceded by the
- An Introduction to the openCyto package
- How to use different auto gating functions
- How to write a csv gating template