An R package suite for microarray meta-analysis in quality control, differentially expressed gene analysis and pathway enrichment detection

Xingbin, Wang; Kang, Dongwan; Shen, Kui; Song, Chi; Lu, Shuya; Chang, Lun‐Ching; Liao, Serena G.; Huo, Zhiguang; Tang, Shaowu; Ding, Ying; Kaminski, Naftali; Sibille, Etienne; Lin, Yan; Li, Jia; Tseng, George C.

doi:10.1093/bioinformatics/bts485

Cited by 185 publications

(197 citation statements)

References 7 publications

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“…CEL files normalized using robust multichip average (23) were subjected to meta-analysis using MetaDE Bioconductor package (https://cran.r-project.org/web/packages/MetaDE/index. html) (27). Normalized expression data along with control and treatment sample labels for each GSE dataset were given as input to meta-analysis function for calculation of z-scores, P-values and the false-discovery rate (FDR) using a random effects model (1,000 permutations; seed value set to 123).…”

Section: Methodsmentioning

confidence: 99%

Functionally conserved effects of rapamycin exposure on zebrafish

Sucularli¹,

Shehwana²,

Kuscu³

et al. 2016

Molecular Medicine Reports

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Abstract. Mechanistic target of rapamycin (mTOR) is a conserved serine/threonine kinase important in cell proliferation, growth and protein translation. Rapamycin, a well-known anti-cancer agent and immunosuppressant drug, inhibits mTOR activity in different taxa including zebrafish. In the present study, the effect of rapamycin exposure on the transcriptome of a zebrafish fibroblast cell line, ZF4, was investigated. Microarray analysis demonstrated that rapamycin treatment modulated a large set of genes with varying functions including protein synthesis, assembly of mitochondrial and proteasomal machinery, cell cycle, metabolism and oxidative phosphorylation in ZF4 cells. A mild however, coordinated reduction in the expression of proteasomal and mitochondrial ribosomal subunits was detected, while the expression of numerous ribosomal subunits increased. Meta-analysis of heterogeneous mouse rapamycin microarray datasets enabled the comparison of zebrafish and mouse pathways modulated by rapamycin, using Kyoto Encyclopedia of Genes and Genomes and Gene Ontology pathway analysis. The analyses demonstrated a high degree of functional conservation between zebrafish and mice in response to rapamycin. In addition, rapamycin treatment resulted in a marked dose-dependent reduction in body size and pigmentation in zebrafish embryos. The present study is the first, to the best of our knowledge, to evaluate the conservation of rapamycin-modulated functional pathways between zebrafish and mice, in addition to the dose-dependent growth curves of zebrafish embryos upon rapamycin exposure.

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Section: Methodsmentioning

confidence: 99%

Functionally conserved effects of rapamycin exposure on zebrafish

Sucularli¹,

Shehwana²,

Kuscu³

et al. 2016

Molecular Medicine Reports

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show abstract

“…20 Genes were ranked by P-value and the top 1000 genes prognostic for metastases were selected from each age cohort. This was used instead of a P-value cutoff as the younger age group was slightly larger and thus had increased statistical power.…”

Section: Nomination Of Metastasis-associated Genes In Age Groupsmentioning

confidence: 99%

High-Throughput Transcriptomic Analysis Nominates Proteasomal Genes As Age Specific Biomarkers and Therapeutic Targets in Prostate Cancer

Zhao

Jackson

Kothari

et al. 2015

International Journal of Radiation Oncology*Biology*Physics

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BACKGROUND: Although prostate cancer (PCa) is hypothesized to differ in nature between younger versus older patients, the underlying molecular distinctions are poorly understood. We hypothesized that high-throughput transcriptomic analysis would elucidate biological differences in PCas arising in younger versus older men, and would nominate potential age-specific biomarkers and therapeutic targets. METHODS: The high-density Affymetrix GeneChip platform, encompassing 41 million genomic loci, was utilized to assess gene expression in 1090 radical prostatectomy samples from patients with long-term follow-up. We identified genes associated with metastatic progression by 10 years post-treatment in younger (ageo65) versus older (age ⩾ 65) patients, and ranked these genes by their prognostic value. We performed Gene Set Enrichment Analysis (GSEA) to nominate biological concepts that demonstrated agespecific effects, and validated a target by treating with a clinically available drug in three PCa cell lines derived from younger men. RESULTS: Over 80% of the top 1000 prognostic genes in younger and older men were specific to that age group. GSEA nominated the proteasome pathway as the most differentially prognostic in younger versus older patients. High expression of proteasomal genes conferred worse prognosis in younger but not older men on univariate and multivariate analysis. Bortezomib, a Food and Drug Administration approved proteasome inhibitor, decreased proliferation in three PCa cell lines derived from younger patients. CONCLUSIONS: Our data show significant global differences in prognostic genes between older versus younger men. We nominate proteasomeal gene expression as an age-specific biomarker and potential therapeutic target specifically in younger men. Limitations of our study include clinical differences between cohorts, and increased comorbidities and lower survival in older patients. These intriguing findings suggest that current models of PCa biology do not adequately represent genetic heterogeneity of PCa related to age, and future clinical trials would benefit from stratification based on age.

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“…• Truncated product method for combining P -values [ 37 ] • t -based modeling [ 38 ] • RankProd [ 39 ] • Meta-analysis based on control of false discovery rate [ 40 ] • Predictor-based approach [ 41 ] • MetaOmics [ 42 ] "systems" approach [ 46 ]. In the "cherry picking" approach, researchers select differentially expressed transcripts for which there is prior biological knowledge.…”

Section: Genome-scale Transcript Profi Lingmentioning

confidence: 99%

Evolving Genomics of Pulmonary Fibrosis

Herazo-Maya

Kaminski

2013

Idiopathic Pulmonary Fibrosis

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Genomic-scale transcript profi ling approaches provide an unbiased view of the transcriptome of organs, tissues, and cells. Such technologies have been applied to the study of lungs and cells of patients with fi brotic lung disease and animal models of lung disease with the goal of detecting key molecules that play a signifi cant role in pathogenesis, identifying potential drug targets, and developing biomarkers of disease presence, progression, and outcome. Genomic profi ling studies have also been used to classify and distinguish different interstitial lung diseases such as IPF, nonspecifi c interstitial pneumonia (NSIP), lung fi brosis associated with scleroderma, and hypersensitivity pneumonitis (HP). In this chapter, we describe the progress and insights derived from applying genomic-scale transcript profi ling approaches to fi brotic lung diseases as well as the potential impact of new technologies and NIH-funded projects on the fi eld of genomics.

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An R package suite for microarray meta-analysis in quality control, differentially expressed gene analysis and pathway enrichment detection

Cited by 185 publications

References 7 publications

Functionally conserved effects of rapamycin exposure on zebrafish

Functionally conserved effects of rapamycin exposure on zebrafish

High-Throughput Transcriptomic Analysis Nominates Proteasomal Genes As Age Specific Biomarkers and Therapeutic Targets in Prostate Cancer

Evolving Genomics of Pulmonary Fibrosis

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