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CD8 T cells are specialized immune cells that play an important role in theregulation of antiviral immune response and the generation of protectiveimmunity. In this paper we investigate the differentiation of memory CD8 Tcells in the immune response using a short time course microarray experiment.Structurally, this experiment is similar to many in that it involvesmeasurements taken on independent samples, in one biological group, at a smallnumber of irregularly spaced time points, and exhibiting patterns of temporalnonstationarity. To analyze this CD8 T-cell experiment, we develop ahierarchical state space model so that we can: (1) detect temporallydifferentially expressed genes, (2) identify the direction of successivechanges over time, and (3) assess the magnitude of successive changes overtime. We incorporate hidden Markov models into our model to utilize theinformation embedded in the time series and set up the proposed hierarchicalstate space model in an empirical Bayes framework to utilize the populationinformation from the large-scale data. Analysis of the CD8 T-cell experimentusing the proposed model results in biologically meaningful findings. Temporalpatterns involved in the differentiation of memory CD8 T cells are summarizedseparately and performance of the proposed model is illustrated in a simulationstudy.

annals of applied statistics/the annals of applied statistics

A statistical analysis of memory CD8 T cell differentiation: An  application of a hierarchical state space model to a short time course  microarray experiment