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  Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis

Llorens, F., Hummel, M., Pastor, X., Ferrer, A., Pluvinet, R., Vivancos, A., et al. (2011). Multiple platform assessment of the EGF dependent transcriptome by microarray and deep tag sequencing analysis. BMC Genomics, 12, 326. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/21699700 http://www.biomedcentral.com/1471-2164/12/326 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3141672/pdf/1471-2164-12-326.pdf?tool=pmcentrez.

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 Creators:
Llorens, F., Author
Hummel, M., Author
Pastor, X., Author
Ferrer, A., Author
Pluvinet, R., Author
Vivancos, A., Author
Castillo, E., Author
Iraola, S., Author
Mosquera, A. M., Author
Gonzalez, E., Author
Lozano, J., Author
Ingham, M., Author
Dohm, J. C.1, Author              
Noguera, M., Author
Kofler, R., Author
del Rio, J. A., Author
Bayes, M., Author
Himmelbauer, H.1, Author              
Sumoy, L., Author
Affiliations:
1Dept. of Vertebrate Genomics (Head: Hans Lehrach), Max Planck Institute for Molecular Genetics, Max Planck Society, ou_1433550              

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Free keywords: Epidermal Growth Factor/*pharmacology; *Gene Expression Profiling; HeLa Cells; Humans; Meta-Analysis as Topic; Metabolic Networks and Pathways/genetics; Metallothionein/genetics/metabolism; Oligonucleotide Array Sequence Analysis/*methods; Sequence Analysis, DNA/*methods; Signal Transduction; Software
 Abstract: BACKGROUND: Epidermal Growth Factor (EGF) is a key regulatory growth factor activating many processes relevant to normal development and disease, affecting cell proliferation and survival. Here we use a combined approach to study the EGF dependent transcriptome of HeLa cells by using multiple long oligonucleotide based microarray platforms (from Agilent, Operon, and Illumina) in combination with digital gene expression profiling (DGE) with the Illumina Genome Analyzer. RESULTS: By applying a procedure for cross-platform data meta-analysis based on RankProd and GlobalAncova tests, we establish a well validated gene set with transcript levels altered after EGF treatment. We use this robust gene list to build higher order networks of gene interaction by interconnecting associated networks, supporting and extending the important role of the EGF signaling pathway in cancer. In addition, we find an entirely new set of genes previously unrelated to the currently accepted EGF associated cellular functions. CONCLUSIONS: We propose that the use of global genomic cross-validation derived from high content technologies (microarrays or deep sequencing) can be used to generate more reliable datasets. This approach should help to improve the confidence of downstream in silico functional inference analyses based on high content data.

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 Dates: 2011
 Publication Status: Published in print
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Title: BMC Genomics
Source Genre: Journal
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Pages: - Volume / Issue: 12 Sequence Number: - Start / End Page: 326 Identifier: ISSN: 1471-2164 (Electronic) 1471-2164 (Linking)