Written by Ryan Brinkman, Ph.D.
Flow cytometry is a powerful screening tool that can be used to help identify target candidates on phenotypically defined cell populations.
There are a myriad of possible assays that can be combined using flow cytometry to examine the effects on these cells. Not to mention the fact that millions of cells can be measured in one experiment, or the statistical power of flow cytometry.
Of course, for these assays to be robust and reproducible within an individual lab, adherence to standard operating procedures and current best practices in flow cytometry is required. New dyes, new protocols, and new reagents are being released on a regular basis and must be titrated, optimized, and validated to ensure high quality data is generated.
Methods sections in scientific papers are often unable to capture all the critical data necessary to accurately reproduce the results in another lab. This continues to exacerbate the concerns Begley and Ellis (and others) raise about reproducibility. Thus, there is growing need to develop methods for communicating more details about the design and execution of an experiment.
In fact, over the last several years, these concerns have surfaced as a critical discussion about the standardization and reproducibility of scientific data. Data that can not be reproduced wastes time, energy and resources.
Why Flow Cytometry Needs Standardization
In their commentary in Nature, Begley and Ellis discuss their experiences in attempting to reproduce ‘landmark’ findings and how only a very low percentage of these were able to be reproduced.
With the pressures to discover new drugs and treatments, this is a huge waste of effort by all concerned, including both academia and industry, and is one of the drivers of the increasing costs of drug discovery. These cost increases led to the National Institutes of Health developing policies to improve rigor and reproducibility in scientific research.
Collins and Tabak discussed this Nature commentary, as did the editor-in-chief of the journal, Science. Soon, as discussed here, new applications to the NIH will be required to address issues of rigor and reproducibility.
The NIH has focused on four areas of reproducibility:
- The scientific premise of the proposed research
- Rigorous experimental design for robust and unbiased results
- Consideration of relevant biological variables
- Authentication of key biological and/or chemical resources
As described below, Dr. Ryan Brinkman provides information on two specific ways in which flow cytometry researchers are effectively communicating the above information to the flow cytometry community to improve reproducibility and consistency.
These two ways include first, the use of the MIFlowCyt standard and second, sharing data using the Flow Repository. This information was recently covered in exceptional detail in a special online lecture that Dr. Ryan Brinkman, a distinguished scientist in the Terry Fox Laboratory at the British Columbia Cancer Agency, and professor of Medical Genetics at the University of British Columbia, delivered to the ExCyte Mastery Class. Enter Dr. Brinkman…
The MIFlowCyt Standard And The FlowRepository
Flow cytometry (FCM) datasets that are currently being generated will be two orders of magnitude larger than any that exist today.
New flow cytometry instruments are available that increase the number of parameters measured for each single cell by to 30. The complexity of such datasets creates challenges in both annotation and data sharing. How do we solve this?
The rapidly expanding availability of FCM datasets through public repositories lays the foundation for researchers to integrate data from multiple research areas and diseases. This is leading to a culture where a large body of annotated and shareable data is available online to the broad biomedical research community. As a result, the development and use of data and metadata (‘data about the data’) standards are critical for achieving this goal.
An important step in curating large FCM datasets is knowing what information needs to be captured. Minimum information guidelines for reporting experiments has found broad-based support (see MIBBI) across biological and technological domains. For flow cytometry data, The Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) effort is now an approved International Society for the Advancement of Cytometry (ISAC) standard and has been adopted by journals, including Cytometry A.
MIFlowCyt provides a checklist covering details including experimental overview, sample description, instrumentation, reagents, and data analysis. Almost all articles now published in Cytometry A follow this recommendation.
Data sharing is also widely recognized as critical by funders and journals including Nature, PLOS and NIH. The FlowRepository is primarily for sharing data associated with peer-reviewed publications annotated according to MIFlowCyt data annotation requirements.
The FlowRepository operates under the auspices of ISAC with guidance provided by ICCS and ESCCA. Together MIFlowCyt and FlowRepository provide a mechanism for researchers to access, review, download, deposit, annotate, share and analyze flow cytometry datasets. This article shares more on how to create a MIFlowCyt compliant manuscript using the FlowRepository.
Since methodology sections in peer-reviewed journal papers often fail to capture all the critical data necessary to accurately reproduce flow cytometry results, efforts have been taken to help flow cytometry researchers improve reproducibility and consistency. Two such efforts are the development and use of the use of the MIFlowCyt standard and second, sharing data using the FlowRepository.
To learn more about publishing your flow cytometry data, and to get access to all of our advanced materials including 20 training videos, presentations, workbooks, and private group membership, get on the Flow Cytometry Mastery Class wait list.