Experiment Overview

Repository ID: FR-FCM-Z5TR Experiment name: Figure 4EFGH MIFlowCyt score: 83.21%
Primary researcher: Vivienne Rebel PI/manager: Vivienne Rebel Uploaded by: Lydia Bederka
Experiment dates: 2018-04-02 - 2022-11-04 Dataset uploaded: Nov 2022 Last updated: Nov 2022
Keywords: [flow cytometry] [Cancer] [automated analysis] [machine learning] [sputum] Manuscripts:
Organizations: UT Health San Antonio Flow Cytometry Core Facility, San Antonio, TX (USA)
Purpose: Describes the selection of live, single cells for analysis of flow cytometry data.
Conclusion: Removal of debris and dead cells is critical for the accuracy of using machine learning approaches and automated analysis.
Comments: None
Funding: bioAffinity Technologies, Inc.
Quality control: Identification of alveolar macrophages to confirm sample adequacy. Presence of alveolar macrophages confirms the sample contains cells derived from the lung and not from the oral cavity.

Experiment variables

Sample Type
· blood concat_BL-18-172_Blood.fcs
· epithelial concat_BL-18-172_Epithelial.fcs

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