Literature DB >> 14739336

Normalization and analysis of cDNA microarrays using within-array replications applied to neuroblastoma cell response to a cytokine.

Jianqing Fan1, Paul Tam, George Vande Woude, Yi Ren.   

Abstract

The quantitative comparison of two or more microarrays can reveal, for example, the distinct patterns of gene expression that define different cellular phenotypes or the genes that are induced in the cellular response to certain stimulations. Normalization of the measured intensities is a prerequisite of such comparisons. However, a fundamental problem in cDNA microarray analysis is the lack of a common standard to compare the expression levels of different samples. Several normalization protocols have been proposed to overcome the variabilities inherent in this technology. We have developed a normalization procedure based on within-array replications via a semilinear in-slide model, which adjusts objectively experimental variations without making critical biological assumptions. The significant analysis of gene expressions is based on a weighted t statistic, which accounts for the heteroscedasticity of the observed log ratios of expressions, and a balanced sign permutation test. We illustrated the use of the techniques in a comparison of the expression profiles of neuroblastoma cells that were stimulated with a growth factor, macrophage migration inhibitory factor (MIF). The analysis of expression changes at mRNA levels showed that approximately 99 genes were up-regulated and 24 were reduced significantly (P <0.001) in MIF-stimulated neuroblastoma cells. The regulated genes included several oncogenes, growth-related genes, tumor metastatic genes, and immuno-related genes. The findings provide clues as to the molecular mechanisms of MIF-mediated tumor progression and supply therapeutic targets for neuroblastoma treatment.

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Year:  2004        PMID: 14739336      PMCID: PMC337019          DOI: 10.1073/pnas.0307557100

Source DB:  PubMed          Journal:  Proc Natl Acad Sci U S A        ISSN: 0027-8424            Impact factor:   11.205


  24 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.  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

3.  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

4.  On differential variability of expression ratios: improving statistical inference about gene expression changes from microarray data.

Authors:  M A Newton; C M Kendziorski; C S Richmond; F R Blattner; K W Tsui
Journal:  J Comput Biol       Date:  2001       Impact factor: 1.479

5.  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

Review 6.  Exploring the new world of the genome with DNA microarrays.

Authors:  P O Brown; D Botstein
Journal:  Nat Genet       Date:  1999-01       Impact factor: 38.330

Review 7.  Tumor growth-promoting properties of macrophage migration inhibitory factor (MIF).

Authors:  R A Mitchell; R Bucala
Journal:  Semin Cancer Biol       Date:  2000-10       Impact factor: 15.707

8.  The human TDE gene homologue: localization to 20q13.1-13.3 and variable expression in human tumor cell lines and tissue.

Authors:  M Bossolasco; M Lebel; N Lemieux; A M Mes-Masson
Journal:  Mol Carcinog       Date:  1999-11       Impact factor: 4.784

9.  Immunohistochemical distribution of inter-alpha-trypsin inhibitor chains in normal and malignant human lung tissue.

Authors:  J Bourguignon; H Borghi; R Sesboüé; M Diarra-Mehrpour; J F Bernaudin; J Métayer; J P Martin; L Thiberville
Journal:  J Histochem Cytochem       Date:  1999-12       Impact factor: 2.479

10.  Intracellular distribution of macrophage migration inhibitory factor predicts the prognosis of patients with adenocarcinoma of the lung.

Authors:  A Kamimura; M Kamachi; J Nishihira; S Ogura; H Isobe; H Dosaka-Akita; A Ogata; M Shindoh; T Ohbuchi; Y Kawakami
Journal:  Cancer       Date:  2000-07-15       Impact factor: 6.860

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  22 in total

1.  NONPARAMETRIC ESTIMATION OF GENEWISE VARIANCE FOR MICROARRAY DATA.

Authors:  Jianqing Fan; Yang Feng; Yue S Niu
Journal:  Ann Stat       Date:  2010-11-01       Impact factor: 4.028

2.  High-resolution spatial normalization for microarrays containing embedded technical replicates.

Authors:  Daniel S Yuan; Rafael A Irizarry
Journal:  Bioinformatics       Date:  2006-10-23       Impact factor: 6.937

3.  Properties of balanced permutations.

Authors:  Lucinda K Southworth; Stuart K Kim; Art B Owen
Journal:  J Comput Biol       Date:  2009-04       Impact factor: 1.479

4.  Computational and analytical framework for small RNA profiling by high-throughput sequencing.

Authors:  Noah Fahlgren; Christopher M Sullivan; Kristin D Kasschau; Elisabeth J Chapman; Jason S Cumbie; Taiowa A Montgomery; Sunny D Gilbert; Mark Dasenko; Tyler W H Backman; Scott A Givan; James C Carrington
Journal:  RNA       Date:  2009-03-23       Impact factor: 4.942

Review 5.  Genetic basis of Hirschsprung's disease.

Authors:  Paul K H Tam; Mercè Garcia-Barceló
Journal:  Pediatr Surg Int       Date:  2009-06-12       Impact factor: 1.827

6.  Identification of differential aberrations in multiple-sample array CGH studies.

Authors:  Huixia Judy Wang; Jianhua Hu
Journal:  Biometrics       Date:  2010-07-09       Impact factor: 2.571

Review 7.  Knockout mouse models of Hirschsprung's disease.

Authors:  J Zimmer; P Puri
Journal:  Pediatr Surg Int       Date:  2015-07-03       Impact factor: 1.827

8.  Integrative Structural Brain Network Analysis in Diffusion Tensor Imaging.

Authors:  Moo K Chung; Jamie L Hanson; Nagesh Adluru; Andrew L Alexander; Richard J Davidson; Seth D Pollak
Journal:  Brain Connect       Date:  2017-06-28

9.  The impact of measurement errors in the identification of regulatory networks.

Authors:  André Fujita; Alexandre G Patriota; João R Sato; Satoru Miyano
Journal:  BMC Bioinformatics       Date:  2009-12-13       Impact factor: 3.169

10.  Spatial normalization improves the quality of genotype calling for Affymetrix SNP 6.0 arrays.

Authors:  High Seng Chai; Terry M Therneau; Kent R Bailey; Jean-Pierre A Kocher
Journal:  BMC Bioinformatics       Date:  2010-06-29       Impact factor: 3.169

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