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. 2015 Jul;87(7):683-7.
doi: 10.1002/cyto.a.22690. Epub 2015 May 14.

ISAC's Gating-ML 2.0 data exchange standard for gating description

Josef Spidlen  1 , Wayne Moore  2 ; ISAC Data Standards Task Force; Ryan R Brinkman  1   3
Collaborators, Affiliations

ISAC's Gating-ML 2.0 data exchange standard for gating description

Josef Spidlen et al. Cytometry A. 2015 Jul.

Abstract

The lack of software interoperability with respect to gating has traditionally been a bottleneck preventing the use of multiple analytical tools and reproducibility of flow cytometry data analysis by independent parties. To address this issue, ISAC developed Gating-ML, a computer file format to encode and interchange gates. Gating-ML 1.5 was adopted and published as an ISAC Candidate Recommendation in 2008. Feedback during the probationary period from implementors, including major commercial software companies, instrument vendors, and the wider community, has led to a streamlined Gating-ML 2.0. Gating-ML has been significantly simplified and therefore easier to support by software tools. To aid developers, free, open source reference implementations, compliance tests, and detailed examples are provided to stimulate further commercial adoption. ISAC has approved Gating-ML as a standard ready for deployment in the public domain and encourages its support within the community as it is at a mature stage of development having undergone extensive review and testing, under both theoretical and practical conditions.

Keywords: bioinformatics; data standard; file format; flow cytometry; gating.

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Conflict of interest statement

Disclosures of Potential Conflicts of Interest: ISAC Data Standards Task Force (DSTF) includes members of companies that make flow cytometry hardware or software. ISAC undertakes to establish standards (i.e. ISAC Recommendations) that do not require the purchase of patent licenses for compliance. For that reason, DSTF members must immediately disclose any patents or patent applications held by them, and which they know, or have reason to believe, have a likelihood of being infringed by compliance with any draft or approved standard. Users and reviewers are also encouraged to disclose any procedures that require a user to purchase a patent license. In addition, by participating in any Task Force, members affirm that, with respect to any patent that may be infringed by compliance with any draft or approved standard and is not disclosed, such patent shall either (1) not be enforced with respect to such compliance, or (2) be freely licensed to all users on a fair, reasonable and non-discriminatory basis without imposing a licensing fee or other charge of any kind. Every Task Force member has pledged to act in good faith and in an open and honest manner at all times.

Figures

Figure 1
Figure 1
Comparison of non-linear scale transformations. All transformations are very similar in the far positive range, where they approximate the logarithmic scale. In the low data range (zoomed-in in the two sub figures), the parameterized inverse hyperbolic sine, Logicle, and Hyperlog transforms show a linear-like behavior around zero and extend the scale to the negative data range. The similarity of these transformations guides a sensible fall back strategy when software does not implement a particular scale.
See this image and copyright information in PMC

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