ArticleBMC genomics2009
Quality control in microarray assessment of gene expression in human airway epithelium.
Article in BMC genomics, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers.
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Who cites it
55 citing papers in PubMed.
- Gene network approach reveals co-expression patterns in nasal and bronchial epithelium.Scientific reports · 2019Trial
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- Development of DNA Microarray for Indication of Viral Community-Acquired Pneumonia Pathogens.Sovremennye tekhnologii v meditsine · 2025Article
- Identification of four key genes related to the diagnosis of chronic obstructive pulmonary disease using bioinformatics analysis.Frontiers in genetics · 2025Article
- Lipolysis engages CD36 to promote ZBP1-mediated necroptosis-impairing lung regeneration in COPD.Cell reports. Medicine · 2024Article
- Review
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- Development of DNA Microarray for Parallel Detection of Community-Acquired Pneumonia Bacterial Pathogens.Sovremennye tekhnologii v meditsine · 2024Article
- Accelerated epigenetic age, inflammation, and gene expression in lung: comparisons of smokers and vapers with non-smokers.Clinical epigenetics · 2023Article
- Stem/Progenitor Cells and Related Therapy in Bronchopulmonary Dysplasia.International journal of molecular sciences · 2023Review
- Adipocyte dysfunction promotes lung inflammation and aberrant repair: a potential target of COPD.Frontiers in endocrinology · 2023Article
- RAB20 Promotes Proliferation via G2/M Phase through the Chk1/cdc25c/cdc2-cyclinB1 Pathway in Penile Squamous Cell Carcinoma.Cancers · 2022Article
- Microarray Data Preprocessing: From Experimental Design to Differential Analysis.Methods in molecular biology (Clifton, N.J.) · 2022Article
- Gene therapy for cystic fibrosis: Challenges and prospects.Frontiers in pharmacology · 2022Review
- Bioinformatic Analysis ofMembranes · 2021Article
- Up-regulation of ACE2, the SARS-CoV-2 receptor, in asthmatics on maintenance inhaled corticosteroids.Respiratory research · 2021Article
- Novel computational analysis of large transcriptome datasets identifies sets of genes distinguishing chronic obstructive pulmonary disease from healthy lung samples.Scientific reports · 2021Article
- Molecular stratification by BCL2A1 and AIM2 provides additional prognostic value in penile squamous cell carcinoma.Theranostics · 2021Article
- Host Factor Interaction Networks Identified by Integrative Bioinformatics Analysis Reveals Therapeutic Implications in COPD Patients With COVID-19.Frontiers in pharmacology · 2021Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
backgroundMicroarray 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) > or = 7.0; (2) cRNA transcript integrity, assessed by signal intensity ratio of GAPDH 3' to 5' probe sets < or = 3.0; and (3) the multi-chip normalization scaling factor < or = 10.0.
resultsOf 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.
conclusionBased 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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