Joint modeling and registration of cell populations in cohorts of high-dimensional flow cytometric data.

ABSTRACT: In biomedical applications, an experimenter encounters different potential sources of variation in data such as individual samples, multiple experimental conditions, and multivariate responses of a panel of markers such as from a signaling network. In multiparametric cytometry, which is often used for analyzing patient samples, such issues are critical. While computational methods can identify cell populations in individual samples, without the ability to automatically match them across samples, it is difficult to compare and characterize the populations in typical experiments, such as those responding to various stimulations or distinctive of particular patients or time-points, especially when there are many samples. Joint Clustering and Matching (JCM) is a multi-level framework for simul

SUBMITTER: Pyne S 

PROVIDER: S-EPMC4077578 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature