Literature DB >> 29305968

Alternatives to current flow cytometry data analysis for clinical and research studies.

Carmen Gondhalekar1, Bartek Rajwa2, Valery Patsekin3, Kathy Ragheb3, Jennifer Sturgis3, J Paul Robinson4.   

Abstract

Flow cytometry has well-established methods for data analysis based on traditional data collection techniques. These techniques typically involved manual insertion of tube samples into an instrument that, historically, could only measure 1-3 colors. The field has since evolved to incorporate new technologies for faster and highly automated sample preparation and data collection. For example, the use of microwell plates on benchtop instruments is now a standard on virtually every new instrument, and so users can easily accumulate multiple data sets quickly. Further, because the user must carefully define the layout of the plate, this information is already defined when considering the analytical process, expanding the opportunities for automated analysis. Advances in multi-parametric data collection, as demonstrated by the development of hyperspectral flow-cytometry, 20-40 color polychromatic flow cytometry, and mass cytometry (CyTOF), are game-changing. As data and assay complexity increase, so too does the complexity of data analysis. Complex data analysis is already a challenge to traditional flow cytometry software. New methods for reviewing large and complex data sets can provide rapid insight into processes difficult to define without more advanced analytical tools. In settings such as clinical labs where rapid and accurate data analysis is a priority, rapid, efficient and intuitive software is needed. This paper outlines opportunities for analysis of complex data sets using examples of multiplexed bead-based assays, drug screens and cell cycle analysis - any of which could become integrated into the clinical environment.
Copyright © 2017. Published by Elsevier Inc.

Keywords:  Data analysis; Drug screens; Flow-cytometry; Hyperspectral cytometry; Multiplexed assays; Plate Analyzer

Mesh:

Year:  2018        PMID: 29305968     DOI: 10.1016/j.ymeth.2017.12.009

Source DB:  PubMed          Journal:  Methods        ISSN: 1046-2023            Impact factor:   3.608


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