ArticleGenome biology2014
An investigation of biomarkers derived from legacy microarray data for their utility in the RNA-seq era.
Article in Genome biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 125 papers.
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Who cites it
125 citing papers in PubMed.
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- GANomics: bridging legacy and modern transcriptomic platforms for clinical applications.NPJ genomic medicine · 2026Article
- Evaluating Cross-Platform Batch Correction Methods for Integrated Microarray and RNA-seq Data Analysis.bioRxiv : the preprint server for biology · 2026Article
- KDM5D expression is lost in cisplatin‑resistant neuroblastoma cells.Oncology reports · 2026Article
- MYCN inhibits TrkC-mediated differentiation in neuroblastoma cells via disruption of the PKA signalling pathway.Cell death discovery · 2026Article
- Ribosomal modifications are associated with mesenchymal fate selection in the neural crest lineage.Nature communications · 2026Article
- Outcome of IWGT workshop on transcriptomic biomarkers for genotoxicity: Key considerations for bioinformatics.Environmental and molecular mutagenesis · 2025Review
- Materiobiology in the omics era.Materials today. Bio · 2025Review
- HIF2α negatively regulates MYCN protein levels and promotes a low-risk noradrenergic phenotype in neuroblastoma.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Restoring mitochondrial quantity and quality to reverse the Warburg effect and drive neuroblastoma differentiation.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Genetic biomarkers and crucial cell subsets of iron metabolism in Beta-Thalassemia: insights from bioinformatics and experimental validation.Annals of hematology · 2025Article
- Bottlenecks in advancing and applying multiomic data integration-common data resources as rate-limiting drivers-the high-impact use case of atherosclerotic cardiovascular disease.Briefings in bioinformatics · 2025Review
- Prognostic implications of store-operated calcium entry signatures and immune dynamics in neuroblastoma via machine learning.Translational cancer research · 2025Article
- Integrated single-cell and bulk RNA sequencing analysis establishes a cancer associated fibroblast-related signature for predicting prognosis and therapeutic responses in neuroblastoma.Discover oncology · 2025Article
- Apoptosis-inducing factor (AIF) at the crossroad of cell survival and cell death: implications for cancer and mitochondrial diseases.Cell communication and signaling : CCS · 2025Review
- GDP-mannose 4,6-dehydratase is a key driver of MYCN-amplified neuroblastoma core fucosylation and tumorigenesis.Oncogene · 2025Article
- Accelerating crop improvement via integration of transcriptome-based network biology and genome editing.Planta · 2025Review
- Sustained cancer-relevant alternative RNA splicing events driven by PRMT5 in high-risk neuroblastoma.Molecular oncology · 2025Article
- Progress in toxicogenomics to protect human health.Nature reviews. Genetics · 2025Review
- Genetic Biomarkers and Circulating White Blood Cells in Osteoarthritis: A Bioinformatics and Mendelian Randomization Analysis.Biomedicines · 2025Article
65 more citing papers are in PubMed but not listed here.
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Authors and funding
19 authors.
Funding
Abstract
backgroundGene expression microarray has been the primary biomarker platform ubiquitously applied in biomedical research, resulting in enormous data, predictive models, and biomarkers accrued. Recently, RNA-seq has looked likely to replace microarrays, but there will be a period where both technologies co-exist. This raises two important questions: Can microarray-based models and biomarkers be directly applied to RNA-seq data? Can future RNA-seq-based predictive models and biomarkers be applied to microarray data to leverage past investment?
resultsWe systematically evaluated the transferability of predictive models and signature genes between microarray and RNA-seq using two large clinical data sets. The complexity of cross-platform sequence correspondence was considered in the analysis and examined using three human and two rat data sets, and three levels of mapping complexity were revealed. Three algorithms representing different modeling complexity were applied to the three levels of mappings for each of the eight binary endpoints and Cox regression was used to model survival times with expression data. In total, 240,096 predictive models were examined.
conclusionsSignature genes of predictive models are reciprocally transferable between microarray and RNA-seq data for model development, and microarray-based models can accurately predict RNA-seq-profiled samples; while RNA-seq-based models are less accurate in predicting microarray-profiled samples and are affected both by the choice of modeling algorithm and the gene mapping complexity. The results suggest continued usefulness of legacy microarray data and established microarray biomarkers and predictive models in the forthcoming RNA-seq era.
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