Merging microarray cell synchronization experiments through curve alignment

The validity of periodic cell cycle regulation studies in plants is seriously compromised by the relatively poor quality of cell synchrony that is achieved for plant suspension cultures in comparison to yeast and mammals. The present state-of-the-art plant synchronization techniques cannot offer a complete cell cycle coverage and moreover a considerable loss of cell synchrony may occur toward the end of the sampling. One possible solution is to consider combining multiple datasets, produced by different synchronization techniques and thus covering different phases of the cell cycle, in order to arrive at a better cell cycle coverage.

We propose a method that enables pasting expression profiles from different plant cell synchronization experiments and results in an expression curve that spans more than one cell cycle. The optimal pasting overlap is determined via a dynamic time warping alignment. Consequently, the different expression time series are merged together by aggregating the corresponding expression values lying within the overlap area. We demonstrate that the periodic analysis of the merged expression profiles produces more reliable p-values for periodicity. Subsequent Gene Ontology analysis of the results confirms that merging synchronization experiments is a more robust strategy for the selection of potentially periodic genes. Additional validation of the proposed algorithm on yeast data is also presented.

Results, benchmark sets and scripts are freely available at our website: http://www.psb.ugent.be/cbd/publications.php