Robust prediction of clinical outcomes using cytometry data.

ABSTRACT:

Motivation

Flow cytometry and mass cytometry are widely used to diagnose diseases and to predict clinical outcomes. When associating clinical features with cytometry data, traditional analysis methods require cell gating as an intermediate step, leading to information loss and susceptibility to batch effects. Here, we wish to explore an alternative approach that predicts clinical features from cytometry data without the cell-gating step. We also wish to test if such a gating-free approach increases the accuracy and robustness of the prediction.

Results

We propose a novel strategy (CytoDx) to predict clinical outcomes using cytometry data without cell gating. Applying CytoDx on real-world datasets allow us to predict multiple types of clinical features. In particular, CytoDx

SUBMITTER: Hu Z 

PROVIDER: S-EPMC6449751 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature