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A dynamic, web-accessible resource to process raw microarray scan data into consolidated gene expression values: importance of replication
Authors:Le Meur Nolwenn  Lamirault Guillaume  Bihouée Audrey  Steenman Marja  Bédrine-Ferran Hélène  Teusan Raluca  Ramstein Gérard  Léger Jean J
Affiliation:Nolwenn Le Meur, Guillaume Lamirault, Audrey Bihouée, Marja Steenman, Hélène Bédrine-Ferran, Raluca Teusan, Gérard Ramstein, and Jean J. Léger
Abstract:We propose a freely accessible web-based pipeline, which processes raw microarray scan data to obtain experimentally consolidated gene expression values. The tool MADSCAN, which stands for MicroArray Data Suites of Computed ANalysis, makes a practical choice among the numerous methods available for filtering, normalizing and scaling of raw microarray expression data in a dynamic and automatic way. Different statistical methods have been adapted to extract reliable information from replicate gene spots as well as from replicate microarrays for each biological situation under study. A carefully constructed experimental design thus allows to detect outlying expression values and to identify statistically significant expression values, together with a list of quality controls with proposed threshold values. The integrated processing procedure described here, based on multiple measurements per gene, is decisive for reliably monitoring subtle gene expression changes typical for most biological events.
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