A Non-parametric Bayesian Model for Joint Cell Clustering and Cluster Matching: Identification of Anomalous Sample Phenotypes with Random Effects.

10.4231/R7KK98PG

Bartlomiej P. Rajwa , Ferit Akova , Halid Ziya Yerebakan , Murat Dundar

09/03/2014

The manuscript presents a non-parametric Bayesian algorithm called ASPIRE (Anomalous Sample Phenotype Identification with Random Effects) able to identify phenotypic differences across batches of cytometry samples in the presence of random effects

AML Bayesian Biomedical Engineering BMC Bioinformatics Computer Science cytometry Dirichlet process Gaussian mixture model Interdisciplinary Research Life Sciences random effects