Lately the importance of flow cytometry as an analytical tool in varied research/clinical areas has widely increased. However, current data standards do not capture the full scope of flow cytometry experiments, i.e., there are no standards to report flow cytometry experiments and thus the experiments are irreproducible and unverifiable by independent researchers. Moreover, the lack of standardization prevents a variety of collaborative opportunities to recreate experimental methods and results.
To address these shortcomings we have brought together a unique cross-disciplinary international collaborative group of bioinformaticists, computational statisticians, software developers and clinician scientists, from both academia and industry (including both software and hardware suppliers) to collaborate on development of data standards in flow cytometry. In conjunction with the ISAC data standards committee and an IEEE Bioinformatics Standards for Flow Cytometry Working Group our goal is to provide consistency in the electronic recording of flow cytometry data analysis. We aim to create universal solutions for representing, collecting, annotating, archiving, analyzing and disseminating flow cytometry data, including the development of open source platform independent software tools verifying our standardization approach as well as serving as reference implementations.
This project is open to community participation. To contributing or follow these efforts join the mailing list, wiki and join the Flow Informatics and Computational Cytometry Society. Please contact Ryan Brinkman with anything related to the standardization effort.
This work has been supported by NIH grant EB005034 from the National Institute of Biomedical Imaging And Bioengineering. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institute of Biomedical Imaging And Bioengineering or the National Institutes of Health.
MIFlowCyt - Minimum Information about a Flow Cytometry Experiment
Standard for outlining the minimum information required to interpret flow cytometry experiments. Please follow the link to download the latest proposal.
ACS - The Analytical Cytometry Standard
The Analytical Cytometry Standard (ACS) proposal standardizes a container format for different components describing analytical cytometry experiments. We are proposing to adopt the ZIP file format as the ACS container file format. Please follow the link to download the latest proposal.
NetCDF - The Network Common Data Form
We have been investigating formats reusable for binary list mode data - one of the components of the proposed ACS container. We believe that the cytometry community could benefit from adopting the Network Common Data Form (NetCDF) for this purpose. NetCDF is a well matured open standard that has been adopted in approximately 30 different fields to accommodate for array-oriented scientific data over the past 20 years. NetCDF is a set of freely available software libraries and machine-independent data formats that support the creation, access, and sharing of array-oriented scientific data. Please see the conventions PDF for motivation and details on how we propose to use NetCDF to capture binary list mode data.
Gating-ML - Gating Description in Flow Cytometry
Gating in flow cytometry is a highly important process for selecting populations of interests by defining the characteristics of particles for further data acquisition or analysis. Gating-ML represents a proposal on how to form unambiguous XML-based gate definitions that can facilitate the interchange and validation of data between different software packages. Gating-ML files are intended to be primarily used within ACS containers. The latest version of Gating-ML includes support for description of compensation and other data transformations.
FuGEFlow - the Functional Genomics Experiment Model extended for Flow Cytometry
OBI - the Ontology for Biomedical Investigations
flow... packages in R
R is a powerful free software environment for statistical computing and graphics. Software tools for analyzing flow cytometry data in R are being developed as part of Bioconductor. See documentation on the flowCore, flowUtils, flowViz etc. packages. These packages are compatible with previous versions of the Gating-ML proposal and are being updated to support the latest version of Gating-ML and ACS.
FACEJava represents a Java reference implementation for initial versions of Gating-ML (and Compensation-ML, Transformation-ML, and FlowRDF, which are now incorporated in Gating-ML but used to be separated proposals). FACEJava is currently being updated to reflect the current ACS, Gating-ML, NetCDF, and other proposals.
We have developed a List Mode Data Converter that performs conversion between files conforming to the Data File Standard for Flow Cytometry ( FCS) and the Network Common Data Form ( NetCDF); Conventions for List Mode Binary Data File. Follow this link to try the List Mode Data Converter.
|Last update: June 22, 2010|