When it comes to data storage, the field of flow cytometry is fairly standardized, thanks to the flow cytometry standard (FCS) file format. The structure of FCS files is described in the FCS specification. Software that strictly complies with the FCS specification is guaranteed to be interoperable (in terms of exchange via FCS files). Nowadays, software interoperability is crucial for eco system, as FCS files are frequently shared, and workflows rely on more than one piece of software (e.g., acquisition and analysis software). Ideally, software developers strictly follow the FCS specification. Unfortunately, this is not always the case, which resulted in various nonconformant FCS files being generated over time. Therefore, robust FCS parsers must be developed, which can handle a wide variety of nonconformant FCS files, from different resources. Development of robust FCS parsers would greatly benefit from a fully fledged set of testing files. In this study, readability of 211,359 public FCS files was evaluated. Each FCS file was checked for conformance with the FCS specification. For each data set, within each FCS file, validated parse results were obtained for the TEXT segment. Highly space efficient testing files were generated. FlowCore was benchmarked in depth, by using the validated parse results, the generated testing files, and the original FCS files. Robustness of FlowCore (as measured by testing against 211,359 files) was improved by re-implementing the TEXT segment parser. Altogether, this study provides a comprehensive resource for FCS parser development, an in-depth benchmark of FlowCore, and a concrete proposal for improving FlowCore.

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doi.org/10.1002/cyto.a.24187, hdl.handle.net/1765/128930
Cytometry. Part A
Department of Immunology

Bras, A.E, & van der Velden, V.H.J. (2020). Robust FCS Parsing: Exploring 211,359 Public Files. Cytometry. Part A. doi:10.1002/cyto.a.24187