Enhanced flowType/RchyOptimyx: a BioConductor pipeline for discovery in high-dimensional cytometry data.
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TLDR
A significantly improved version of the flowType and RchyOptimyx BioConductor-based pipeline is presented that is both 14 times faster and can accommodate multiple levels of biomarker expression for up to 96 markers, positioned to be an integral part of data analysis for high-throughput experiments on high-dimensional single-cell assay platforms.Abstract:
We present a significantly improved version of the flowType and RchyOptimyx BioConductor-based pipeline that is both 14 times faster and can accommodate multiple levels of biomarker expression for up to 96 markers. With these improvements, the pipeline is positioned to be an integral part of data analysis for high-throughput experiments on high-dimensional single-cell assay platforms, including flow cytometry, mass cytometry and single-cell RT-qPCR.read more
Citations
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Automated analysis of flow cytometry data comes of age
Ryan R. Brinkman,Ryan R. Brinkman,Nima Aghaeepour,Greg Finak,Raphael Gottardo,Tim R. Mosmann,Richard H. Scheuermann,Richard H. Scheuermann +7 more
TL;DR: The results of the FlowCAP-IV study are important as they highlight the significant value of unsupervised analysis approaches that can mine the full high dimensional flow cytometry data.
Journal ArticleDOI
Key steps and methods in the experimental design and data analysis of highly multi-parametric flow and mass cytometry
TL;DR: This review presents the most recent FC and MC computational approaches that are used to prepare, process and interpret high-content cytometry data and underscores proper experimental design as a key step for obtaining good quality data.
Journal ArticleDOI
High throughput automated analysis of big flow cytometry data
Albina Rahim,Justin Meskas,Sibyl Drissler,Alice Yue,Anna Lorenc,Adam Laing,Namita Saran,Jacqui White,Lucie Abeler-Dörner,Adrian Hayday,Ryan R. Brinkman,Ryan R. Brinkman +11 more
TL;DR: This work reviews the components of a customized automated analysis pipeline that can be generally applied to large scale flow cytometry data and demonstrates these methodologies on data collected by the International Mouse Phenotyping Consortium (IMPC).
Journal ArticleDOI
flowCL: ontology-based cell population labelling in flow cytometry
Mélanie Courtot,Justin Meskas,Alexander D. Diehl,Radina Droumeva,Raphael Gottardo,Adrin Jalali,Mohammad Jafar Taghiyar,Holden T. Maecker,J. Philip McCoy,Alan Ruttenberg,Richard H. Scheuermann,Richard H. Scheuermann,Ryan R. Brinkman +12 more
TL;DR: By providing automated labelling of cell populations based on their immunophenotype, flowCL allows for unambiguous and reproducible identification of standardized cell types.
Journal ArticleDOI
Deep profiling of multitube flow cytometry data
Kieran O'Neill,Nima Aghaeepour,Jeremy Parker,Donna E. Hogge,Aly Karsan,Bakul I. Dalal,Ryan R. Brinkman +6 more
TL;DR: FlowBin this paper allocates cells to bins defined by the common markers across tubes in a multitube experiment, then computes aggregate expression for each bin within each tube, to create a matrix of expression of all markers assayed in each tube.
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