Analysing time course microarray data using Bioconductor: a case study using yeast2 Affymetrix arrays

BACKGROUND: Large scale microarray experiments are becoming increasingly routine, particularly those which track a number of different cell lines through time. This time-course information provides valuable insight into the dynamic mechanisms underlying the biological processes being observed. However, proper statistical analysis of time-course data requires the use of more sophisticated tools and complex statistical models. FINDINGS: Using the open source CRAN and Bioconductor repositories for R, we provide example analysis and protocol which illustrate a variety of methods that can be used to analyse time-course microarray data. In particular, we highlight how to construct appropriate contrasts to detect differentially expressed genes and how to generate plausible pathways from the data. A maintained version of the R commands can be found at http://www.mas.ncl.ac.uk/~ncsg3/microarray/. CONCLUSIONS: CRAN and Bioconductor are stable repositories that provide a wide variety of appropriate statistical tools to analyse time course microarray data.