Dataset Information
FlowCL: ontology-based cell population labelling in flow cytometry.
Ontology highlight
ABSTRACT: Motivation
Finding one or more cell populations of interest, such as those correlating to a specific disease, is critical when analysing flow cytometry data. However, labelling of cell populations is not well defined, making it difficult to integrate the output of algorithms to external knowledge sources.Results
We developed flowCL, a software package that performs semantic labelling of cell populations based on their surface markers and applied it to labelling of the Federation of Clinical Immunology Societies Human Immunology Project Consortium lyoplate populations as a use case.Conclusion
By providing automated labelling of cell populations based on their immunophenotype, flowCL allows for unambiguous and reproducible identification of standardized cell types.Availability and implementation
Code, R script and documentation are available under the Artistic 2.0 license through Bioconductor (http://www.bioconductor.org/packages/devel/bioc/html/flowCL.html).Contact
rbrinkman@bccrc.caSupplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Courtot M
PROVIDER: S-EPMC4393520 | biostudies-literature | 2015 Apr
REPOSITORIES: biostudies-literature
Publications
flowCL: ontology-based cell population labelling in flow cytometry.
Bioinformatics (Oxford, England) 20141206 8
<h4>Motivation</h4>Finding one or more cell populations of interest, such as those correlating to a specific disease, is critical when analysing flow cytometry data. However, labelling of cell populations is not well defined, making it difficult to integrate the output of algorithms to external knowledge sources.<h4>Results</h4>We developed flowCL, a software package that performs semantic labelling of cell populations based on their surface markers and applied it to labelling of the Federation ...[more]
