Multi-set Pre-processing of Multicolor Flow Cytometry Data.

ABSTRACT: Flow Cytometry is an analytical technology to simultaneously measure multiple markers per single cell. Ten thousands to millions of single cells can be measured per sample and each sample may contain a different number of cells. All samples may be bundled together, leading to a 'multi-set' structure. Many multivariate methods have been developed for Flow Cytometry data but none of them considers this structure in their quantitative handling of the data. The standard pre-processing used by existing multivariate methods provides models mainly influenced by the samples with more cells, while such a model should provide a balanced view of the biomedical information within all measurements. We propose an alternative 'multi-set' preprocessing that corrects for the difference in number of cells m

SUBMITTER: Folcarelli R 

PROVIDER: S-EPMC7297713 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature