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A large variety of methods has been proposed in the literature for microarray data analysis. The aim of this paper was to present techniques used by the EADGENE (European Animal Disease Genomics Network of Excellence) WP1.4 participants for data quality control, normalisation and statistical methods for the detection of differentially expressed genes in(More)
Microarrays allow researchers to measure the expression of thousands of genes in a single experiment. Before statistical comparisons can be made, the data must be assessed for quality and normalisation procedures must be applied, of which many have been proposed. Methods of comparing the normalised data are also abundant, and no clear consensus has yet been(More)
The aim of this paper was to describe, and when possible compare, the multivariate methods used by the participants in the EADGENE WP1.4 workshop. The first approach was for class discovery and class prediction using evidence from the data at hand. Several teams used hierarchical clustering (HC) or principal component analysis (PCA) to identify groups of(More)
In this paper we propose a new procedure to select differentially expressed genes between several conditions in microarray experiments. Asymptotic properties for the false discovery rate are proved under mild conditions. We compare by simulations and on a pseudo-real data set our procedure to the Benjamini and Hochberg's procedure and a procedure based on(More)
3 Merci aussi aux trois autres mousquetaires : Anne, Bérengère et Françoise, pour les discussions " entre filles " , au cours de nos petits repas du midi. Je suis reconnaissante aussì a ma copine thèsarde, Kim-Anh, avec laquelle j'ai partagé mesprobì emes de doctorante et d'enseignante, ellé etait un réel soutien pour moi. C'est maintenantà mes parents et(More)
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