QFMatch: multidimensional flow and mass cytometry samples alignment

Creators: Orlova, Darya Y.; Meehan, Stephen; Parks, David; Moore, Wayne A.; Meehan, Connor; Zhao, Qian; Ghosn, Eliver E. B.; Herzenberg, Leonore A.; Walther, Guenther

Abstract

Part of the flow/mass cytometry data analysis process is aligning (matching) cell subsets between relevant samples. Current methods address this cluster-matching problem in ways that are either computationally expensive, affected by the curse of dimensionality, or fail when population patterns significantly vary between samples. Here, we introduce a quadratic form (QF)-based cluster matching algorithm (QFMatch) that is computationally efficient and accommodates cases where population locations differ significantly (or even disappear or appear) from sample to sample. We demonstrate the effectiveness of QFMatch by evaluating sample datasets from immunology studies. The algorithm is based on a novel multivariate extension of the quadratic form distance for the comparison of flow cytometry data sets. We show that this QF distance has attractive computational and statistical properties that make it well suited for analysis tasks that involve the comparison of flow/mass cytometry samples.

Additional Information

© 2018 The Author(s). This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. Received: 08 June 2017. Accepted: 05 February 2018. Published online: 19 February 2018. We thank the members of the Herzenberg laboratory for advice and help in the interpretation of flow cytometry data. Further, we thank John Mantovani for excellent administrative help. This work was supported by NIH Training Grant [5 T32 AI007290-32]. Author Contributions: D.Y.O., S.M., D.P., W.M., L.A.H., G.W.: Conception and design; Analysis and interpretation of the data; Drafting of the article; Critical revision of the article for important intellectual content. C.M.: Conception and design; Drafting of the article; Critical revision of the article for important intellectual content. E.E.B.G.: Conception and design of experiments; Analysis and interpretation of the data; Drafting of the article; Critical revision of the article for important intellectual content. Q.Z.: Conception and design; Simulation study. The authors declare no competing interests.

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