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Quality control in microarray assessment of gene expression in human airway epithelium

BACKGROUND: Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment o...

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Autores principales: Raman, Tina, O'Connor, Timothy P, Hackett, Neil R, Wang, Wei, Harvey, Ben-Gary, Attiyeh, Marc A, Dang, David T, Teater, Matthew, Crystal, Ronald G
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2009
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2774870/
https://www.ncbi.nlm.nih.gov/pubmed/19852842
http://dx.doi.org/10.1186/1471-2164-10-493
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author Raman, Tina
O'Connor, Timothy P
Hackett, Neil R
Wang, Wei
Harvey, Ben-Gary
Attiyeh, Marc A
Dang, David T
Teater, Matthew
Crystal, Ronald G
author_facet Raman, Tina
O'Connor, Timothy P
Hackett, Neil R
Wang, Wei
Harvey, Ben-Gary
Attiyeh, Marc A
Dang, David T
Teater, Matthew
Crystal, Ronald G
author_sort Raman, Tina
collection PubMed
description BACKGROUND: Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n = 223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals and hybridized to Affymetrix microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥ 7.0; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤ 3.0; and (3) the multi-chip normalization scaling factor ≤ 10.0. RESULTS: Of the 223 samples, all three criteria were assessed in 191; of these 184 (96.3%) passed all three criteria. For the remaining 32 samples, the RIN was not available, and only the other two criteria were used; of these 29 (90.6%) passed these two criteria. Correlation coefficients for pairwise comparisons of expression levels for 100 maintenance genes in which at least one array failed the QC criteria (average Pearson r = 0.90 ± 0.04) were significantly lower (p < 0.0001) than correlation coefficients for pairwise comparisons between arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). Inter-array variability was significantly decreased (p < 0.0001) among samples passing the QC criteria compared with samples failing the QC criteria. CONCLUSION: Based on the aberrant maintenance gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data, and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation.
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spelling pubmed-27748702009-11-10 Quality control in microarray assessment of gene expression in human airway epithelium Raman, Tina O'Connor, Timothy P Hackett, Neil R Wang, Wei Harvey, Ben-Gary Attiyeh, Marc A Dang, David T Teater, Matthew Crystal, Ronald G BMC Genomics Research Article BACKGROUND: Microarray technology provides a powerful tool for defining gene expression profiles of airway epithelium that lend insight into the pathogenesis of human airway disorders. The focus of this study was to establish rigorous quality control parameters to ensure that microarray assessment of the airway epithelium is not confounded by experimental artifact. Samples (total n = 223) of trachea, large and small airway epithelium were collected by fiberoptic bronchoscopy of 144 individuals and hybridized to Affymetrix microarrays. The pre- and post-chip quality control (QC) criteria established, included: (1) RNA quality, assessed by RNA Integrity Number (RIN) ≥ 7.0; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets ≤ 3.0; and (3) the multi-chip normalization scaling factor ≤ 10.0. RESULTS: Of the 223 samples, all three criteria were assessed in 191; of these 184 (96.3%) passed all three criteria. For the remaining 32 samples, the RIN was not available, and only the other two criteria were used; of these 29 (90.6%) passed these two criteria. Correlation coefficients for pairwise comparisons of expression levels for 100 maintenance genes in which at least one array failed the QC criteria (average Pearson r = 0.90 ± 0.04) were significantly lower (p < 0.0001) than correlation coefficients for pairwise comparisons between arrays that passed the QC criteria (average Pearson r = 0.97 ± 0.01). Inter-array variability was significantly decreased (p < 0.0001) among samples passing the QC criteria compared with samples failing the QC criteria. CONCLUSION: Based on the aberrant maintenance gene data generated from samples failing the established QC criteria, we propose that the QC criteria outlined in this study can accurately distinguish high quality from low quality data, and can be used to delete poor quality microarray samples before proceeding to higher-order biological analyses and interpretation. BioMed Central 2009-10-24 /pmc/articles/PMC2774870/ /pubmed/19852842 http://dx.doi.org/10.1186/1471-2164-10-493 Text en Copyright © 2009 Raman et al; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( (http://creativecommons.org/licenses/by/2.0) ), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Raman, Tina
O'Connor, Timothy P
Hackett, Neil R
Wang, Wei
Harvey, Ben-Gary
Attiyeh, Marc A
Dang, David T
Teater, Matthew
Crystal, Ronald G
Quality control in microarray assessment of gene expression in human airway epithelium
title Quality control in microarray assessment of gene expression in human airway epithelium
title_full Quality control in microarray assessment of gene expression in human airway epithelium
title_fullStr Quality control in microarray assessment of gene expression in human airway epithelium
title_full_unstemmed Quality control in microarray assessment of gene expression in human airway epithelium
title_short Quality control in microarray assessment of gene expression in human airway epithelium
title_sort quality control in microarray assessment of gene expression in human airway epithelium
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2774870/
https://www.ncbi.nlm.nih.gov/pubmed/19852842
http://dx.doi.org/10.1186/1471-2164-10-493
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