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Robust FCS Parsing: Exploring 211,359 Public Files

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 (...

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Autores principales: Bras, Anne E., van der Velden, Vincent H. J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754493/
https://www.ncbi.nlm.nih.gov/pubmed/32633075
http://dx.doi.org/10.1002/cyto.a.24187
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author Bras, Anne E.
van der Velden, Vincent H. J.
author_facet Bras, Anne E.
van der Velden, Vincent H. J.
author_sort Bras, Anne E.
collection PubMed
description 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. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals LLC on behalf of International Society for Advancement of Cytometry.
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spelling pubmed-77544932020-12-28 Robust FCS Parsing: Exploring 211,359 Public Files Bras, Anne E. van der Velden, Vincent H. J. Cytometry A Technical Notes 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. © 2020 The Authors. Cytometry Part A published by Wiley Periodicals LLC on behalf of International Society for Advancement of Cytometry. John Wiley & Sons, Inc. 2020-07-15 2020-11 /pmc/articles/PMC7754493/ /pubmed/32633075 http://dx.doi.org/10.1002/cyto.a.24187 Text en © 2020 The Authors. Cytometry Part A published by Wiley Periodicals LLC on behalf of International Society for Advancement of Cytometry. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Technical Notes
Bras, Anne E.
van der Velden, Vincent H. J.
Robust FCS Parsing: Exploring 211,359 Public Files
title Robust FCS Parsing: Exploring 211,359 Public Files
title_full Robust FCS Parsing: Exploring 211,359 Public Files
title_fullStr Robust FCS Parsing: Exploring 211,359 Public Files
title_full_unstemmed Robust FCS Parsing: Exploring 211,359 Public Files
title_short Robust FCS Parsing: Exploring 211,359 Public Files
title_sort robust fcs parsing: exploring 211,359 public files
topic Technical Notes
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7754493/
https://www.ncbi.nlm.nih.gov/pubmed/32633075
http://dx.doi.org/10.1002/cyto.a.24187
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