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Publishing code is essential for reproducible flow cytometry bioinformatics

ON behalf of the International Society for the Advancement of Cytometry, Cytometry Part A has instituted a Software Policy for manuscripts that include software for the analysis of flow cytometry data (1). These requirements include open source licensing, deposition of both code and test data, testing on standard data where applicable, and provision of all instructions necessary to install and execute code. This represents a major step forward toward reproducible flow cytometry bioinformatics. The ability to reproduce experiments is an essential part of the scientific process. For those of us working in FCM, reproducibility means providing key pieces of information, including details about the instrument used, the samples tested, and the analysis performed on the resulting data. The Minimum Information About a Flow Cytometry Experiment (MIFlowCyt) provides a set of guidelines for this purpose (2), and its use has been mandated by several publishers, including Wiley & Sons, publisher of Cytometry Part A. However, MIFlowCyt is focused mainly on wet lab components of the experiment. Although primary data along with compensation and gating details are also required to be shared, this is only sufficient for low-dimensional, low-throughput studies. With recent technological advances, data sets are growing by orders of magnitude, requiring bioinformatics tools such as those highlighted in a recent special issue in this journal (3). As analyses become more complex, so, too, does the task of ensuring that they can be reliably reproduced. What are the important details of computational analysis of FCM data that need to be captured, and how should they be provided? MIFlowCyt suggests providing the “exact mathematical formulas/algorithms” (2) for each of these, and allows for this information to be provided as text. However, MIFlowCyt is only intended to allow for understanding of the experiment (and analysis), not for reproducibility. What else is needed? This problem has received more attention in the broader biostatistics community, where reproducible research has been defined as “research papers with accompanying software tools that allow the reader to directly reproduce the results and employ the computational methods that are presented in the research article” (4). Or, put another way, in much the same way as lab protocols provided in a methods section should be sufficient to reproduce bench results, manuscripts should come with code and accompanying data which, when run, will reproduce the figures and tables in the article.