ArticleJournal of computational biology : a journal of computational molecular cell biology2017
A Joint Bayesian Model for Integrating Microarray and RNA Sequencing Transcriptomic Data.
Article in Journal of computational biology : a journal of computational molecular cell biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 2 of them syntheses that pooled it.
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Who cites it
16 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Transcriptomic Landscape and Regulatory Pathways of Drought Response in Rice (International journal of molecular sciences · 2026Pooled it
- Meta-Analysis of Two Human RNA-seq Datasets to Determine Periodontitis Diagnostic Biomarkers and Drug Target Candidates.International journal of molecular sciences · 2022Pooled it
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- RNA Sequencing of Pooled Samples Effectively Identifies Differentially Expressed Genes.Biology · 2023Article
- Comprehensive transcriptomic analysis to identify biological and clinical differences in cholangiocarcinoma.Cancer medicine · 2023Article
- C1QA, C1QB, and GZMB are novel prognostic biomarkers of skin cutaneous melanoma relating tumor microenvironment.Scientific reports · 2022Article
- CENPF/CDK1 signaling pathway enhances the progression of adrenocortical carcinoma by regulating the G2/M-phase cell cycle.Journal of translational medicine · 2022Article
- Centromere Protein F (Journal of Cancer · 2021Article
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- Platform-integrated mRNA isoform quantification.Bioinformatics (Oxford, England) · 2020Article
- Comprehensive analysis of transcriptome data for identifying biomarkers and therapeutic targets in head and neck squamous cell carcinoma.Annals of translational medicine · 2020Article
- Article
- Integrated Microarray and RNAseq Transcriptomic Analysis of Retinal Pigment Epithelium/Choroid in Age-Related Macular Degeneration.Frontiers in cell and developmental biology · 2020Article
- Integrated analysis highlights multiple long non‑coding RNAs and their potential roles in the progression of human esophageal squamous cell carcinoma.Oncology reports · 2019Article
- Transcriptomic and functional network features of lung squamous cell carcinoma through integrative analysis of GEO and TCGA data.Scientific reports · 2018Article
Corrections and comments
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Authors and funding
4 authors.
Funding
Abstract
As the sequencing cost continued to drop in the past decade, RNA sequencing (RNA-seq) has replaced microarray to become the standard high-throughput experimental tool to analyze transcriptomic profile. As more and more datasets are generated and accumulated in the public domain, meta-analysis to combine multiple transcriptomic studies to increase statistical power has received increasing popularity. In this article, we propose a Bayesian hierarchical model to jointly integrate microarray and RNA-seq studies. Since systematic fold change differences across RNA-seq and microarray for detecting differentially expressed genes have been previously reported, we replicated this finding in several real datasets and showed that incorporation of a normalization procedure to account for the bias improves the detection accuracy and power. We compared our method with the popular two-stage Fisher's method using simulations and two real applications in a histological subtype (invasive lobular carcinoma) of breast cancer comparing PR+ versus PR- and early-stage versus late-stage patients. The result showed improved detection power and more significant and interpretable pathways enriched in the detected biomarkers from the proposed Bayesian model.
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