Simple methods for peak and valley detection in time series microarray data

Given a set of gene expression time series obtained by a microarray experiment, this work proposes a novel quality control procedure, which exploits some analytical methods enabling the identification of genes which spike expressions within narrow time-windows and over a chosen amplitude threshold. The procedure automatically provides a list of genes and time points in which abrupt variations have been detected. The quality control has to be performed by a biologist, who assesses those spikes as bearing biology relevance or being artifacts. In the latter case spikes have to be substituted by a smoothing procedure. In particular, we focused on transcriptome of Plasmodium falciparum Intraerythrocytic Developmental Cycle. Assuming that spikes detected in this set have been labeled as artifacts by a biologist, in the second part of this paper we discuss the effects of smoothing on subsequent different types of analyses