Publishing code is essential for reproducible flow cytometry bioinformatics

O’Neill, Kieran; Brinkman, Ryan R.

doi:10.1002/cyto.a.22805

Cited by 10 publications

(7 citation statements)

References 12 publications

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“…This stresses also the importance of the reproducibility in complex, (semi)‐automated data analysis . O'Neill and Brinkman have suggested that certain data besides compensation, gating details and mathematical algorithms, should be shared for reproducible FCM bioinformatics . One major aim is to make FCM data easily accessible to the users by open‐access databases for flow data (e.g., FlowRepository ), as well as the code sources.…”

Section: Data Handling Evaluation Storage and Repositoriesmentioning

confidence: 99%

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

et al. 2019

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These guidelines are a consensus work of a considerable number of members of the immunology and flow cytometry community. They provide the theory and key practical aspects of flow cytometry enabling immunologists to avoid the common errors that often undermine immunological data. Notably, there are comprehensive sections of all major immune cell types with helpful Tables detailing phenotypes in murine and human cells. The latest flow cytometry techniques and applications are also described, featuring examples of the data that can be generated and, importantly, how the data can be analysed. Furthermore, there are sections detailing tips, tricks and pitfalls to avoid, all written and peer‐reviewed by leading experts in the field, making this an essential research companion.

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Section: Data Handling Evaluation Storage and Repositoriesmentioning

confidence: 99%

Guidelines for the use of flow cytometry and cell sorting in immunological studies (second edition)

et al. 2019

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“…Importantly, these packages support automated data preprocessing (cleaning) and can be organized into multipackage pipelines. Use of these tools and deposition of the raw data into public data repositories (such as FlowRepository) directly address the need for increased rigor, reproducibility, and transparency in flow cytometric studies ( 46 , 47 ). Importantly, almost all of these powerful tools are available at no cost.…”

Section: Analysis and Data Presentationmentioning

confidence: 99%

Improving the Quality and Reproducibility of Flow Cytometry in the Lung. An Official American Thoracic Society Workshop Report

Tighe

Redente

et al. 2019

Am J Respir Cell Mol Biol

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Defining responses of the structural and immune cells in biologic systems is critically important to understanding disease states and responses to injury. This requires accurate and sensitive methods to define cell types in organ systems. The principal method to delineate the cell populations involved in these processes is flow cytometry. Although researchers increasingly use flow cytometry, technical challenges can affect its accuracy and reproducibility, thus significantly limiting scientific advancements. This challenge is particularly critical to lung immunology, as the lung is readily accessible and therefore used in preclinical and clinical studies to define potential therapeutics. Given the importance of flow cytometry in pulmonary research, the American Thoracic Society convened a working group to highlight issues and technical challenges to the performance of high-quality pulmonary flow cytometry, with a goal of improving its quality and reproducibility.

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“…Conventional data analysis of flow cytometry data is repetitive and laborintensive, lacks transparency and is susceptible to bias. Particularly in the context of large clinical trials, in which data acquisition can occur longitudinally over a long time period, sometimes on different instruments and at multiple centers (1,2), the ability to use a programmatic gating strategy not only is more transparent and reproducible but also facilitates better quality control that improve interpretation of the data (3)(4)(5).…”

Section: Introductionmentioning

confidence: 99%