| Literature DB >> 30570217 |
Valerie K Conrad1, Christopher J Dubay1, Mehrnoush Malek2, Ryan R Brinkman2,3, Yoshinobu Koguchi1, William L Redmond1.
Abstract
Automated reagent preparation, sample processing, and data acquisition have increased the rate at which flow cytometry data can be generated. Furthermore, advances in technology and flow cytometry instrumentation continually increase the complexity and dimensionality of this data. Together, this leads to increased pressure on manual data analysis, which has inherent limitations including subjectivity of the analyst and the length of time needed for data processing. These issues can create bottlenecks in the data processing workflow and potentially compromise data quality. To address these issues, as well as the challenges associated with manual gating in a high-volume human immune profiling laboratory, we sought to implement an automated analysis pipeline. In this report, we discuss considerations for selecting an automated analysis method, the process of implementing an automated pipeline, and detail our successful incorporation of an automated gating strategy with flowDensity into our analysis workflow. This validated pipeline augments our laboratory's ability to provide rapid high-throughput immune profiling for patients participating in cancer immunotherapy clinical trials. © International Society for Advancement of Cytometry. © International Society for Advancement of Cytometry.Entities:
Keywords: T cells; automated analysis; automated gating; cancer; flowDensity; immune profiling; immunotherapy
Mesh:
Year: 2018 PMID: 30570217 DOI: 10.1002/cyto.a.23664
Source DB: PubMed Journal: Cytometry A ISSN: 1552-4922 Impact factor: 4.355