Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Transcription profiling of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays to compare combining gene expression data from different generations of oligonucleotide arrays

ABSTRACT: Compatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different generations of microarrays can be combined more effectively. The dataset of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays for this purpose. Signal values from GCOS 1.2 with Detection call and p-value are provided here, and CEL files are also available for download.

ORGANISM(S): Homo sapiens

SUBMITTER: Sek Won Kong

PROVIDER: E-GEOD-2044 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Combining gene expression data from different generations of oligonucleotide arrays.

Hwang Kyu-Baek KB Kong Sek Won SW Greenberg Steve A SA Park Peter J PJ

BMC bioinformatics 20041025

<h4>Background</h4>One of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data ev ...[more]

PMID: 15504239

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Project description:BackgroundOne of the important challenges in microarray analysis is to take full advantage of previously accumulated data, both from one's own laboratory and from public repositories. Through a comparative analysis on a variety of datasets, a more comprehensive view of the underlying mechanism or structure can be obtained. However, as we discover in this work, continual changes in genomic sequence annotations and probe design criteria make it difficult to compare gene expression data even from different generations of the same microarray platform.ResultsWe first describe the extent of discordance between the results derived from two generations of Affymetrix oligonucleotide arrays, as revealed in cluster analysis and in identification of differentially expressed genes. We then propose a method for increasing comparability. The dataset we use consists of a set of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays. We find that the use of the probe set matching table for comparative analysis provided by Affymetrix produces better results than matching by UniGene or LocusLink identifiers but still remains inadequate. Rescaling of expression values for each gene across samples and data filtering by expression values enhance comparability but only for few specific analyses. As a generic method for improving comparability, we select a subset of probes with overlapping sequence segments in the two array types and recalculate expression values based only on the selected probes. We show that this filtering of probes significantly improves the comparability while retaining a sufficient number of probe sets for further analysis.ConclusionsCompatibility between high-density oligonucleotide arrays is significantly affected by probe-level sequence information. With a careful filtering of the probes based on their sequence overlaps, data from different generations of microarrays can be combined more effectively.

Project description:Upregulation of Expression of the Ubiquitin Carboxyl Terminal Hydrolase L1 Gene in Human Airway Epithelium of Cigarette Smokers The microarray data deposited here is from 11 HG-U133A GeneChips, from 5 normal non-smokers and 6 phenotypic normal smokers, large airways. Samples from the small airways of these individuals have been obtained and analyzed using the HG-U133A GeneChip; the small airway samples are in GEO Accession Number GSE 3320, and the data analysis is described in Harvey, B-G; Heguy, A.; Leopold, P.L.; Carolan, B.; Ferris, B. and Crystal R.G. Modification of Gene Expression of the Small Airway Epithelium in Response to Cigarette Smoking. J. Mol. Med (in press). These data are part of a study aimed at understanding how cigarette smoking modifies neuroendocrine cells, in which microarray analysis with TaqMan confirmation was used to assess airway epithelial samples obtained by fiberoptic bronchoscopy from 81 individuals (normal nonsmokers, normal smokers, smokers with early COPD and smokers with established COPD). Of 11 genes considered to be neuroendocrine cell-specific, only ubiquitin C-terminal hydrolase L1(UCHL1), a member of the ubiquitin proteasome pathway, was consistently upregulated in smokers compared to nonsmokers. Up-regulation of UCHL1 at the protein level was observed with immunohistochemistry of bronchial biopsies of smokers compared to nonsmokers. Interestingly, however, while UCHL1 expression was present only in neuroendocrine cells of the airway epithelium in nonsmokers, UCHL1 expression was also expressed in ciliated epithelial cells in smokers, an intriguing observation in light of recent observations that ciliated cells can are capable of transdifferentiating to other airway epithelium. In the context that UCHL1 is involved in the degradation of unwanted, misfolded or damaged proteins within the cell and is overexpressed in >50% of lung cancers, its overexpression in chronic smokers may represent an early event in the complex transformation from normal epithelium to overt malignancy. Keywords: smokers vs non-smokers

Dataset Information

Transcription profiling of 14 human muscle biopsy samples from patients with inflammatory myopathies that were hybridized on both HG-U95Av2 and HG-U133A human arrays to compare combining gene expression data from different generations of oligonucleotide arrays

Publications

Combining gene expression data from different generations of oligonucleotide arrays.

Similar Datasets

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