ArticleBMC bioinformatics2011
Identifier mapping performance for integrating transcriptomics and proteomics experimental results.
Article in BMC bioinformatics, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 59 papers.
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Who cites it
59 citing papers in PubMed.
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- Expression and prognosis of NR3C1 in uterine corpus endometrial carcinoma based on multiple datasets.Discover oncology · 2025Article
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- The combined signatures of G protein-coupled receptor family and immune landscape provide a prognostic and therapeutic biomarker in endometrial carcinoma.Journal of cancer research and clinical oncology · 2023Article
- Is HOXA5 a Novel Prognostic Biomarker for Uterine Corpus Endometrioid Adenocarcinoma?International journal of molecular sciences · 2023Article
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- TRPS1 regulates the opposite effect of progesterone via RANKL in endometrial carcinoma and breast carcinoma.Cell death discovery · 2023Article
- PPP1R14B is a diagnostic prognostic marker in patients with uterine corpus endometrial carcinoma.Journal of cellular and molecular medicine · 2023Article
- CXCR3 predicts the prognosis of endometrial adenocarcinoma.BMC medical genomics · 2023Article
- Identification of novel key genes associated with uterine corpus endometrial carcinoma progression and prognosis.Annals of translational medicine · 2023Article
- Synaptotagmin-like protein 1 is a potential diagnostic and prognostic biomarker in endometrial cancer based on bioinformatics and experiments.Journal of ovarian research · 2023Article
- GAPDH: A common housekeeping gene with an oncogenic role in pan-cancer.Computational and structural biotechnology journal · 2023Article
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
backgroundStudies integrating transcriptomic data with proteomic data can illuminate the proteome more clearly than either separately. Integromic studies can deepen understanding of the dynamic complex regulatory relationship between the transcriptome and the proteome. Integrating these data dictates a reliable mapping between the identifier nomenclature resultant from the two high-throughput platforms. However, this kind of analysis is well known to be hampered by lack of standardization of identifier nomenclature among proteins, genes, and microarray probe sets. Therefore data integration may also play a role in critiquing the fallible gene identifications that both platforms emit.
resultsWe compared three freely available internet-based identifier mapping resources for mapping UniProt accessions (ACCs) to Affymetrix probesets identifications (IDs): DAVID, EnVision, and NetAffx. Liquid chromatography-tandem mass spectrometry analyses of 91 endometrial cancer and 7 noncancer samples generated 11,879 distinct ACCs. For each ACC, we compared the retrieval sets of probeset IDs from each mapping resource. We confirmed a high level of discrepancy among the mapping resources. On the same samples, mRNA expression was available. Therefore, to evaluate the quality of each ACC-to-probeset match, we calculated proteome-transcriptome correlations, and compared the resources presuming that better mapping of identifiers should generate a higher proportion of mapped pairs with strong inter-platform correlations. A mixture model for the correlations fitted well and supported regression analysis, providing a window into the performance of the mapping resources. The resources have added and dropped matches over two years, but their overall performance has not changed.
conclusionsThe methods presented here serve to achieve concrete context-specific insight, to support well-informed decisions in choosing an ID mapping strategy for "omic" data merging.
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Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.