Literature DB >> 15475389

A dynamic, web-accessible resource to process raw microarray scan data into consolidated gene expression values: importance of replication.

Nolwenn Le Meur1, Guillaume Lamirault, Audrey Bihouée, Marja Steenman, Hélène Bédrine-Ferran, Raluca Teusan, Gérard Ramstein, 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.

Mesh:

Year:  2004        PMID: 15475389      PMCID: PMC524282          DOI: 10.1093/nar/gkh870

Source DB:  PubMed          Journal:  Nucleic Acids Res        ISSN: 0305-1048            Impact factor:   16.971


  22 in total

1.  Significance analysis of microarrays applied to the ionizing radiation response.

Authors:  V G Tusher; R Tibshirani; G Chu
Journal:  Proc Natl Acad Sci U S A       Date:  2001-04-17       Impact factor: 11.205

2.  Normalization strategies for cDNA microarrays.

Authors:  J Schuchhardt; D Beule; A Malik; E Wolski; H Eickhoff; H Lehrach; H Herzel
Journal:  Nucleic Acids Res       Date:  2000-05-15       Impact factor: 16.971

Review 3.  Analysis of cDNA microarray images.

Authors:  Y H Yang; M J Buckley; T P Speed
Journal:  Brief Bioinform       Date:  2001-12       Impact factor: 11.622

4.  Minimum information about a microarray experiment (MIAME)-toward standards for microarray data.

Authors:  A Brazma; P Hingamp; J Quackenbush; G Sherlock; P Spellman; C Stoeckert; J Aach; W Ansorge; C A Ball; H C Causton; T Gaasterland; P Glenisson; F C Holstege; I F Kim; V Markowitz; J C Matese; H Parkinson; A Robinson; U Sarkans; S Schulze-Kremer; J Stewart; R Taylor; J Vilo; M Vingron
Journal:  Nat Genet       Date:  2001-12       Impact factor: 38.330

5.  Issues in cDNA microarray analysis: quality filtering, channel normalization, models of variations and assessment of gene effects.

Authors:  G C Tseng; M K Oh; L Rohlin; J C Liao; W H Wong
Journal:  Nucleic Acids Res       Date:  2001-06-15       Impact factor: 16.971

6.  Normalization for cDNA microarray data: a robust composite method addressing single and multiple slide systematic variation.

Authors:  Yee Hwa Yang; Sandrine Dudoit; Percy Luu; David M Lin; Vivian Peng; John Ngai; Terence P Speed
Journal:  Nucleic Acids Res       Date:  2002-02-15       Impact factor: 16.971

7.  Analysis of altered gene expression in rat soleus muscle atrophied by disuse.

Authors:  N Cros; A V Tkatchenko; D F Pisani; L Leclerc; J J Léger; J F Marini; C A Dechesne
Journal:  J Cell Biochem       Date:  2001 Aug 21-Sep 5       Impact factor: 4.429

8.  Analysis of variance for gene expression microarray data.

Authors:  M K Kerr; M Martin; G A Churchill
Journal:  J Comput Biol       Date:  2000       Impact factor: 1.479

9.  Importance of replication in microarray gene expression studies: statistical methods and evidence from repetitive cDNA hybridizations.

Authors:  M L Lee; F C Kuo; G A Whitmore; J Sklar
Journal:  Proc Natl Acad Sci U S A       Date:  2000-08-29       Impact factor: 11.205

10.  Large-scale analysis of differential gene expression in the hindlimb muscles and diaphragm of mdx mouse.

Authors:  A V Tkatchenko; G Le Cam; J J Léger; C A Dechesne
Journal:  Biochim Biophys Acta       Date:  2000-01-03
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Journal:  BMC Med Genomics       Date:  2009-11-10       Impact factor: 3.063

2.  SimArray: a user-friendly and user-configurable microarray design tool.

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5.  Gene expression profiling of Spodoptera frugiperda hemocytes and fat body using cDNA microarray reveals polydnavirus-associated variations in lepidopteran host genes transcript levels.

Authors:  M Barat-Houari; F Hilliou; F-X Jousset; L Sofer; E Deleury; J Rocher; M Ravallec; L Galibert; P Delobel; R Feyereisen; P Fournier; A-N Volkoff
Journal:  BMC Genomics       Date:  2006-06-21       Impact factor: 3.969

6.  Systematic analysis of blood cell transcriptome in end-stage chronic respiratory diseases.

Authors:  Julie Chesné; Richard Danger; Karine Botturi; Martine Reynaud-Gaubert; Sacha Mussot; Marc Stern; Isabelle Danner-Boucher; Jean-François Mornex; Christophe Pison; Claire Dromer; Romain Kessler; Marcel Dahan; Olivier Brugière; Jérôme Le Pavec; Frédéric Perros; Marc Humbert; Carine Gomez; Sophie Brouard; Antoine Magnan
Journal:  PLoS One       Date:  2014-10-20       Impact factor: 3.240

7.  Acute induction of cell death-related IFN stimulated genes (ISG) differentiates highly from moderately virulent CSFV strains.

Authors:  Patricia Renson; Yannick Blanchard; Mireille Le Dimna; Hélène Felix; Roland Cariolet; André Jestin; Marie-Frédérique Le Potier
Journal:  Vet Res       Date:  2009-10-01       Impact factor: 3.683

8.  Image analysis and data normalization procedures are crucial for microarray analyses.

Authors:  Ali Kpatcha Kadanga; Christine Leroux; Muriel Bonnet; Stéphanie Chauvet; Bruno Meunier; Isabelle Cassar-Malek; Jean-François Hocquette
Journal:  Gene Regul Syst Bio       Date:  2008-03-17

9.  Transcriptomic and proteomic analyses of seasonal photoperiodism in the pea aphid.

Authors:  G Le Trionnaire; F Francis; S Jaubert-Possamai; J Bonhomme; E De Pauw; J-P Gauthier; E Haubruge; F Legeai; N Prunier-Leterme; J-C Simon; S Tanguy; D Tagu
Journal:  BMC Genomics       Date:  2009-09-29       Impact factor: 3.969

10.  Comparative profiling of the sense and antisense transcriptome of maize lines.

Authors:  Jiong Ma; Darren J Morrow; John Fernandes; Virginia Walbot
Journal:  Genome Biol       Date:  2006-03-13       Impact factor: 13.583

  10 in total

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