Merging microarray cell synchronization experiments through curve alignment.
BACKGROUND
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.


RESULTS
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.


BACKGROUND
Results, benchmark sets and scripts are freely available at our website: http://www.psb.ugent.be/cbd/publications.php
Hermans
Filip
F
Computational Biology Division, Department of Plant Systems Biology Flanders Institute for Biotechnology, Technologiepark 917, 9052 Ghent, Belgium. fiher@psb.ugent.be
Tsiporkova
Elena
E
D000465:Algorithms; D017360:Arabidopsis / Q000166:cytology* / Q000235:genetics / Q000378:metabolism*; D029681:Arabidopsis Proteins / Q000235:genetics / Q000378:metabolism*; D002453:Cell Cycle / Q000502:physiology*; D018797:Cell Cycle Proteins / Q000378:metabolism*; D003198:Computer Simulation; D020869:Gene Expression Profiling / Q000379:methods; D016247:Information Storage and Retrieval / Q000379:methods; D008954:Models, Biological; D009716:Numerical Analysis, Computer-Assisted; D020411:Oligonucleotide Array Sequence Analysis / Q000379:methods*
D029681:Arabidopsis Proteins; D018797:Cell Cycle Proteins