ArticleBMC genomics2010
Comparison and consolidation of microarray data sets of human tissue expression.
Article in BMC genomics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 1 of them a synthesis that pooled it.
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Who cites it
18 citing papers in PubMed, 1 synthesis or guideline pooled it, 29 citations in OpenAlex.
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- Comparison of multiple transcriptomes exposes unified and divergent features of quiescent and activated skeletal muscle stem cells.Skeletal muscle · 2017Article
- HDNetDB: A Molecular Interaction Database for Network-Oriented Investigations into Huntington's Disease.Scientific reports · 2017Article
- PPARγ targeted oral cancer treatment and additional utility of genomics analytic techniques.The Laryngoscope · 2017Article
- A benchmark of gene expression tissue-specificity metrics.Briefings in bioinformatics · 2017Article
- The Transcriptional Landscape of the Photosynthetic Model Cyanobacterium Synechocystis sp. PCC6803.Scientific reports · 2016Article
- Blood-based identification of non-responders to anti-TNF therapy in rheumatoid arthritis.BMC medical genomics · 2015Article
- Sex-related gene expression profiles in the adrenal cortex in the mature rat: microarray analysis with emphasis on genes involved in steroidogenesis.International journal of molecular medicine · 2015Article
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- The use of transcriptomics to unveil the role of nutrients in Mammalian liver.ISRN nutrition · 2013Review
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- Evaluation of candidate genes from orphan FEB and GEFS+ loci by analysis of human brain gene expression atlases.PloS one · 2011Article
Corrections and comments
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Authors and funding
2 authors at 2 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundHuman tissue displays a remarkable diversity in structure and function. To understand how such diversity emerges from the same DNA, systematic measurements of gene expression across different tissues in the human body are essential. Several recent studies addressed this formidable task using microarray technologies. These large tissue expression data sets have provided us an important basis for biomedical research. However, it is well known that microarray data can be compromised by high noise level and various experimental artefacts. Critical comparison of different data sets can help to reveal such errors and to avoid pitfalls in their application.
resultsWe present here the first comparison and integration of four freely available tissue expression data sets generated using three different microarray platforms and containing a total of 377 microarray hybridizations. When assessing the tissue expression of genes, we found that the results considerably depend on the chosen data set. Nevertheless, the comparison also revealed statistically significant similarity of gene expression profiles across different platforms. This enabled us to construct consolidated lists of platform-independent tissue-specific genes using a set of complementary measures. Follow-up analyses showed that results based on consolidated data tend to be more reliable.
conclusionsOur study strongly indicates that the consolidation of the four different tissue expression data sets can increase data quality and can lead to biologically more meaningful results. The provided compendium of platform-independent gene lists should facilitate the identification of novel tissue-specific marker genes.
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