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.
Subject(s)
Gene Expression Profiling/methods , Oligonucleotide Array Sequence Analysis/methods , Software , Data Interpretation, Statistical , Gene Expression Profiling/standards , Humans , Internet , Male , Oligonucleotide Array Sequence Analysis/standards , Quality Control , Reproducibility of ResultsABSTRACT
Complete clinical expression of the HFE1 hemochromatosis is very likely modulated by genes linked to duodenal iron absorption, whose level is conditioned by unknown processes taking place during enterocyte differentiation. We carried out a transcriptomic study on CaCo-2 cells used as a model of enterocyte differentiation in vitro. Of the 720 genes on the microarrays, 80, 50, and 56 were significantly down-regulated up-regulated, and invariant during differentiation. With regard to iron metabolism, we showed that HEPH, SLC11A2, SLC11A3, and TF are significantly up-regulated, while ATP7B and SLC39A1 (and SFT) are down-regulated and ACO1, dCYTb, FECH, and FTH1 show constant expression. Ontological annotations highlight the decrease in the expression of cell cycle and DNA metabolism associated genes as well as transcription, protein metabolism, signal transduction, and nucleocytoplasmic transport associated genes, whereas there are increases in the expression of genes linked to cell adhesion, lipid and xenobiotic metabolism, iron transport and homeostasis, and immune response.
