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Experiment Overview

Repository ID: FR-FCM-ZYTT Experiment name: Predicting cell populations in single cell mass cytometry data MIFlowCyt score: 27.00%
Primary researcher: Tamim Abdelaal PI/manager: Tamim Abdelaal Uploaded by: Tamim Abdelaal
Experiment dates: 2017-10-02 - Dataset uploaded: Dec 2018 Last updated: Dec 2018
Keywords: [mass cytometry] [machine learning] [single-cell] [Cell population prediction] Manuscripts: [30861637] Cytalogo
Organizations: Delft University of Technology, Delft Bioinformatics Lab, Delft, Zuid Holland (Netherlands)
Purpose: Automatic prediction of cell populations in mass cytometry data, using supervised learning algorithms
Conclusion: Linear Discriminant Analysis classifier can accurately predict abundant and rare cell populations, and outperforms semi-supervised and deep learning methods.
Comments: All data files are uploaded in CSV format.
Funding: European Commission of a H2020 MSCA award under proposal number 675743 (ISPIC)
Quality control: None
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