Print Email Facebook Twitter CyTOFmerge Title CyTOFmerge: integrating mass cytometry data across multiple panels Author Abdelaal, T.R.M. (TU Delft Pattern Recognition and Bioinformatics; Leiden University Medical Center) Höllt, T. (TU Delft Computer Graphics and Visualisation; Leiden University Medical Center) van Unen, Vincent (Leiden University Medical Center) Lelieveldt, B.P.F. (TU Delft Pattern Recognition and Bioinformatics; Leiden University Medical Center) Koning, Frits (Leiden University Medical Center) Reinders, M.J.T. (TU Delft Pattern Recognition and Bioinformatics; Leiden University Medical Center) Mahfouz, A.M.E.T.A. (TU Delft Pattern Recognition and Bioinformatics; Leiden University Medical Center) Date 2019 Abstract Motivation: High-dimensional mass cytometry (CyTOF) allows the simultaneous measurement of multiple cellular markers at single-cell level, providing a comprehensive view of cell compositions.However, the power of CyTOF to explore the full heterogeneity of a biological sample at the singlecell level is currently limited by the number of markers measured simultaneously on a single panel.Results: To extend the number of markers per cell, we propose an in silico method to integrate CyTOF datasets measured using multiple panels that share a set of markers. Additionally, we present an approach to select the most informative markers from an existing CyTOF dataset to be used as a shared marker set between panels. We demonstrate the feasibility of our methods byevaluating the quality of clustering and neighborhood preservation of the integrated dataset, on two public CyTOF datasets. We illustrate that by computationally extending the number of markerswe can further untangle the heterogeneity of mass cytometry data, including rare cell-population detection. To reference this document use: http://resolver.tudelft.nl/uuid:035d9501-e58c-4f76-9dde-aa01cff16f04 DOI https://doi.org/10.1093/bioinformatics/btz180 ISSN 1367-4803 Source Bioinformatics, 35 (20), 4063-4071 Part of collection Institutional Repository Document type journal article Rights © 2019 T.R.M. Abdelaal, T. Höllt, Vincent van Unen, B.P.F. Lelieveldt, Frits Koning, M.J.T. Reinders, A.M.E.T.A. Mahfouz Files PDF btz180.pdf 6.29 MB Close viewer /islandora/object/uuid:035d9501-e58c-4f76-9dde-aa01cff16f04/datastream/OBJ/view