Please read Drs. Wei and Tian’s article in Annals of Applied Statistics titled, “An empirical Bayes change-point model for transcriptome time-course data.“
Gene expression temporal patterns can reveal regulation networks. The transcriptome time-course experiment measures thousands of gene expression levels during relatively few time points. In such experiments, the number of time points is usually small, such as three to 20. Many such experiments are not replicated due to cost and other limitations, and, when replicates are available, the numbers are typically also small. Technologies for measuring genes include microarrays and RNA-seq. These technologies have been used to
capture the temporal gene expression fluctuations in many biological processes, such as regulation of development, immune responses, and tissue inflammation programs. To read the full article.
An empirical Bayes change-point model for transcriptome time-course data. Tian T, Cheng RH, Wei Z. Ann. Appl. Stat. 15 (1) 509 – 526, March 2021. DOI: 10.1214/20-AOAS1403