scholarly journals Bayesian Mixture Model Analysis for Detecting Differentially Expressed Genes

2008 ◽  
Vol 2008 ◽  
pp. 1-12 ◽  
Author(s):  
Zhenyu Jia ◽  
Shizhong Xu
Keyword(s):  
Mixture Model ◽  
Differentially Expressed Genes ◽  
Differential Expression Analysis ◽  
Differentially Expressed ◽  
Control Treatment ◽  
Microarray Gene Expression ◽  
Bayesian Mixture Model ◽  
Bayesian Mixture ◽  
Truncated Normal ◽  
Upregulated Genes

Control-treatment design is widely used in microarray gene expression experiments. The purpose of such a design is to detect genes that express differentially between the control and the treatment. Many statistical procedures have been developed to detect differentially expressed genes, but all have pros and cons and room is still open for improvement. In this study, we propose a Bayesian mixture model approach to classifying genes into one of three clusters, corresponding to clusters of downregulated, neutral, and upregulated genes, respectively. The Bayesian method is implemented via the Markov chain Monte Carlo (MCMC) algorithm. The cluster means of down- and upregulated genes are sampled from truncated normal distributions whereas the cluster mean of the neutral genes is set to zero. Using simulated data as well as data from a real microarray experiment, we demonstrate that the new method outperforms all methods commonly used in differential expression analysis.

Potential genes and pathways along with immune cells infiltration in the progression of atherosclerosis identified via microarray gene expression dataset re-analysis

Vascular ◽  
2020 ◽  
Vol 28 (5) ◽  
pp. 643-654 ◽  
Author(s):  
Jing Xu ◽  
Yuejin Yang
Keyword(s):  
Differentially Expressed Genes ◽  
Immune Cells ◽  
Interaction Network ◽  
Wilcoxon Test ◽  
Differentially Expressed ◽  
P Value ◽  
The Novel ◽  
Microarray Gene Expression ◽  
Progression Of Atherosclerosis ◽  
Geo Database

Objective Atherosclerosis is a chronic inflammatory process characterized by the accumulation and formation of lipid-rich plaques within the layers of the arterial wall. Although numerous studies have reported the underlying pathogenesis, no data-based studies have been conducted to analyze the potential genes and immune cells infiltration in the different stages of atherosclerosis via bioinformatics analysis. Methods In this study, we downloaded GSE100927 and GSE28829 from NCBI-GEO database. Gene ontology and pathway enrichment were performed via the DAVID database. The protein interaction network was constructed via STRING. Enriched hub genes were analyzed by the Cytoscape software. The evaluation of the infiltrating immune cells in the dataset samples was performed by the CIBERSORT algorithm. Results We identified 114 common upregulated differentially expressed genes and 22 common downregulated differentially expressed genes. (adjust p value < 0.01 and log FC ≥ 1). A cluster of 10 genes including CYBA, SLC11A1, FCER1G, ITGAM, ITGB2, CD53, ITGAX, VAMP8, CLEC5A, and CD300A were found to be significant. Through the deconvolution algorithm CIBERSORT, we analyzed the significant alteration of immune cells infiltration in the progression of atherosclerosis with the threshold of the Wilcoxon test at p value <0.05. Conclusions These results may reveal the underlying correlations between genes and immune cells in atherosclerosis, which enable us to investigate the novel insights for the development of treatments and drugs.

scholarly journals Transcriptome profiling of posterior kidney of brown trout, Salmo trutta, during proliferative kidney disease

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Arun Sudhagar ◽  
Reinhard Ertl ◽  
Gokhlesh Kumar ◽  
Mansour El-Matbouli
Keyword(s):  
Immune System ◽  
Kidney Disease ◽  
Differentially Expressed Genes ◽  
Brown Trout ◽  
Salmo Trutta ◽  
Differentially Expressed ◽  
Rna Seq ◽  
Proliferative Kidney Disease ◽  
Immune System Process ◽  
Upregulated Genes

Abstract Background Tetracapsuloides bryosalmonae is a myxozoan parasite which causes economically important and emerging proliferative kidney disease (PKD) in salmonids. Brown trout, Salmo trutta is a native fish species of Europe, which acts as asymptomatic carriers for T. bryosalmonae. There is only limited information on the molecular mechanism involved in the kidney of brown trout during T. bryosalmonae development. We employed RNA sequencing (RNA-seq) to investigate the global transcriptome changes in the posterior kidney of brown trout during T. bryosalmonae development. Methods Brown trout were exposed to the spores of T. bryosalmonae and posterior kidneys were collected from both exposed and unexposed control fish. cDNA libraries were prepared from the posterior kidney and sequenced. Bioinformatics analysis was performed using standard pipeline of quality control, reference mapping, differential expression analysis, gene ontology, and pathway analysis. Quantitative real time PCR was performed to validate the transcriptional regulation of differentially expressed genes, and their correlation with RNA-seq data was statistically analyzed. Results Transcriptome analysis identified 1169 differentially expressed genes in the posterior kidney of brown trout, out of which 864 genes (74%) were upregulated and 305 genes (26%) were downregulated. The upregulated genes were associated with the regulation of immune system process, vesicle-mediated transport, leucocyte activation, and transport, whereas the downregulated genes were associated with endopeptidase regulatory activity, phosphatidylcholine biosynthetic process, connective tissue development, and collagen catabolic process. Conclusion To our knowledge, this is the first RNA-seq based transcriptome study performed in the posterior kidney of brown trout during active T. bryosalmonae development. Most of the upregulated genes were associated with the immune system process, whereas the downregulated genes were associated with other metabolic functions. The findings of this study provide insights on the immune responses mounted by the brown trout on the developing parasite, and the host molecular machineries modulated by the parasite for its successful multiplication and release.

Bayesian Mixture Model for Prediction of Bus Arrival Time

2015 ◽  
Vol 6 (6) ◽  
pp. 961
Author(s):  
Misbahuddin Misbahuddin ◽  
Riri Fitri Sari
Keyword(s):  
Mixture Model ◽  
Arrival Time ◽  
Bayesian Mixture Model ◽  
Bayesian Mixture

scholarly journals Coiled-Coil Domain Containing 80 Suppresses Nonylphenol-Induced Colorectal Cancer Cell Proliferation by Inhibiting the Activation of ERK1/2

2021 ◽  
Vol 9 ◽  
Author(s):  
Jing Wang ◽  
Yuan-wei Zhang ◽  
Nian-jie Zhang ◽  
Shuo Yin ◽  
Du-ji Ruan ◽  
...  
Keyword(s):  
Colorectal Cancer ◽  
Cell Proliferation ◽  
Cell Growth ◽  
Differentially Expressed Genes ◽  
Endocrine Disrupting Chemicals ◽  
Coiled Coil ◽  
Underlying Mechanism ◽  
Differentially Expressed ◽  
Coiled Coil Domain ◽  
Upregulated Genes

Recently, the effect of endocrine-disrupting chemicals on the cancer procession has been a concern. Nonylphenol (NP) is a common environmental estrogen that has been shown to enhance the proliferation of colorectal cancer (CRC) cells in our previous studies; however, the underlying mechanism remains unclear. In this study, we confirmed the increased concentration of NP in the serum of patients with CRC. RNA sequencing was used to explore the differentially expressed genes after NP exposure. We found 16 upregulated genes and 12 downregulated genes in COLO205 cells after NP treatment. Among these differentially expressed genes, we found that coiled-coil domain containing 80 (CCDC80) was downregulated by NP treatment and was associated with CRC progression. Further experiments revealed that the overexpression of CCDC80 significantly suppressed NP-induced cell proliferation and recovered the reduced cell apoptosis. Meanwhile, the overexpression of CCDC80 significantly inhibited the activation of ERK1/2 induced by NP treatment. ERK1/2 inhibitor (PD98059) treatment also suppressed NP-induced CRC cell growth, but the overexpression of CCDC80 did not enhance the effect of ERK1/2 inhibitor. Taken together, NP treatment significantly inhibited the expression of CCDC80, and the overexpression of CCDC80 suppressed NP-induced CRC cell growth by inhibiting the activation of ERK1/2. These results suggest that NP could induce CRC cell growth by influencing the expression of multiple genes. CCDC80 and ERK1/2 inhibitors may be suitable therapeutic targets in NP-related CRC progression.

scholarly journals Integrative Analysis for Elucidating Transcriptomics Landscapes of Systemic Lupus Erythematosus

2021 ◽  
Vol 12 ◽  
Author(s):  
Haihong Zhang ◽  
Yanli Wang ◽  
Jinghui Feng ◽  
Shuya Wang ◽  
Yan Wang ◽  
...  
Keyword(s):  
Systemic Lupus Erythematosus ◽  
Differentially Expressed Genes ◽  
Lupus Erythematosus ◽  
Differential Expression Analysis ◽  
Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Integrated Analysis ◽  
Potential Candidate ◽  
Systemic Lupus

Systemic lupus erythematosus (SLE) is a complex and heterogeneous autoimmune disease that the immune system attacks healthy cells and tissues. SLE is difficult to get a correct and timely diagnosis, which makes its morbidity and mortality rate very high. The pathogenesis of SLE remains to be elucidated. To clarify the potential pathogenic mechanism of SLE, we performed an integrated analysis of two RNA-seq datasets of SLE. Differential expression analysis revealed that there were 4,713 and 2,473 differentially expressed genes, respectively, most of which were up-regulated. After integrating differentially expressed genes, we identified 790 common differentially expressed genes (DEGs). Gene functional enrichment analysis was performed and found that common differentially expressed genes were significantly enriched in some important immune-related biological processes and pathways. Our analysis provides new insights into a better understanding of the pathogenic mechanisms and potential candidate markers for systemic lupus erythematosus.

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