scholarly journals RNA-Seq Data Analysis in Galaxy

2021 ◽  
pp. 367-392
Author(s):  
Bérénice Batut ◽  
Marius van den Beek ◽  
Maria A. Doyle ◽  
Nicola Soranzo
Keyword(s):  
Data Analysis ◽  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Rna Seq ◽  
Web Interface ◽  
Bioinformatics Analyses ◽  
The Galaxy ◽  
Data Upload

AbstractA complete RNA-Seq analysis involves the use of several different tools, with substantial software and computational requirements. The Galaxy platform simplifies the execution of such bioinformatics analyses by embedding the needed tools in its web interface, while also providing reproducibility. Here, we describe how to perform a reference-based RNA-Seq analysis using Galaxy, from data upload to visualization and functional enrichment analysis of differentially expressed genes.

scholarly journals bcbioRNASeq: R package for bcbio RNA-seq analysis

F1000Research ◽  
2017 ◽  
Vol 6 ◽  
pp. 1976 ◽  
Author(s):  
Michael J. Steinbaugh ◽  
Lorena Pantano ◽  
Rory D. Kirchner ◽  
Victor Barrera ◽  
Brad A. Chapman ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
R Package ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Control Analysis ◽  
Rna Seq ◽  
Sequencing Data ◽  
Post Process

RNA-seq analysis involves multiple steps from processing raw sequencing data to identifying, organizing, annotating, and reporting differentially expressed genes. bcbio is an open source, community-maintained framework providing automated and scalable RNA-seq methods for identifying gene abundance counts. We have developed bcbioRNASeq, a Bioconductor package that provides ready-to-render templates and wrapper functions to post-process bcbio output data. bcbioRNASeq automates the generation of high-level RNA-seq reports, including identification of differentially expressed genes, functional enrichment analysis and quality control analysis.

scholarly journals Identification of nine key genes by bioinformatics analysis for predicting poor prognosis in smoking-induced lung adenocarcinoma

2020 ◽  
Vol 9 (2) ◽  
pp. LMT30
Author(s):  
Chuanli Ren ◽  
Weixiu Sun ◽  
Xu Lian ◽  
Chongxu Han
Keyword(s):  
Lung Adenocarcinoma ◽  
Differentially Expressed Genes ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Kaplan Meier ◽  
Key Genes ◽  
Core Genes

Aim: To screen and identify key genes related to the development of smoking-induced lung adenocarcinoma (LUAD). Materials & methods: We obtained data from the GEO chip dataset GSE31210. The differentially expressed genes were screened by GEO2R. The protein interaction network of differentially expressed genes was constructed by STRING and Cytoscape. Finally, core genes were screened. The overall survival time of patients with the core genes was analyzed by Kaplan–Meier method. Gene ontology and Kyoto encyclopedia of genes and genomes bioaccumulation was calculated by DAVID. Results: Functional enrichment analysis indicated that nine key genes were actively involved in the biological process of smoking-related LUAD. Conclusion: 23 core genes and nine key genes among them were correlated with adverse prognosis of LUAD induced by smoking.

scholarly journals Comparative transcriptomic analysis of porcine peripheral blood reveals differentially expressed genes from the cytokine–cytokine receptor interaction pathway related to health status

Genome ◽  
2017 ◽  
Vol 60 (12) ◽  
pp. 1021-1028 ◽  
Author(s):  
M.H. Ye ◽  
H. Bao ◽  
Y. Meng ◽  
L.L. Guan ◽  
P. Stothard ◽  
...  
Keyword(s):  
Health Status ◽  
Differentially Expressed Genes ◽  
Peripheral Blood ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Cytokine Receptor ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Receptor Interaction ◽  
Marker Genes

While some research has looked into the host genetic response in pigs challenged with specific viruses or bacteria, few studies have explored the expression changes of transcripts in the peripheral blood of sick pigs that may be infected with multiple pathogens on farms. In this study, the architecture of the peripheral blood transcriptome of 64 Duroc sired commercial pigs, including 18 healthy animals at entry to a growing facility (set as a control) and 23 pairs of samples from healthy and sick pen mates, was generated using RNA-Seq technology. In total, 246 differentially expressed genes were identified to be specific to the sick animals. Functional enrichment analysis for those genes revealed that the over-represented gene ontology terms for the biological processes category were exclusively immune activity related. The cytokine–cytokine receptor interaction pathway was significantly enriched. Nine functional genes from this pathway encoding members (as well as their receptors) of the interleukins, chemokines, tumor necrosis factors, colony stimulating factors, activins, and interferons exhibited significant transcriptional alteration in sick animals. Our results suggest a subset of novel marker genes that may be useful candidate genes in the evaluation and prediction of health status in pigs under commercial production conditions.

scholarly journals Identification of associated molecular events in Helicobacter pylori infection and gastric cancer through integrated computational analysis of Microarray and RNA-Seq datasets

2021 ◽  
Author(s):  
Sabaoon Zeb ◽  
Rehan Zafar Paracha ◽  
Maryum Nisar ◽  
Rimsha Khalid ◽  
Zartasha Mustansar ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Helicobacter Pylori ◽  
Cancer Progression ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
World Health ◽  
Separate Analysis ◽  
Rna Seq ◽  
Molecular Events

Abstract According to the World Health Organization, Gastric cancer (GC) is the third leading cause of death worldwide, where, the major precursor of cancer progression is infection with Helicobacter pylori. It has been reported that 50% of the total populace is infected with H.pylori, while in 80% the ulcer emerges in later stages of the infection. Although extensive separate analysis has been performed on H.pylori infection and GC data, however, there is a need to perform comparative analysis to identify the cross-talk between the conditions and to hunt significant molecular events that occurs during H.pylori induced GC. The aim of this multi-population study was to identify common molecular events and potential bio-markers against H.pylori induced GC. We performed microarray and RNA-seq analysis on publicly available H.pylori infection, gastritis, H.pylori induced GC and GC datasets to obtain Differentially Expressed Genes (DEGs). After obtaining the DEGs, integrative analysis, functional enrichment analysis and network biology approaches were utilized to identify common markers and hub genes between various disease conditions. Functional enrichment analysis revealed the DEGs of H.pylori infection, gastritis, H.pylori induced GC and GC were strongly associated with spliceosome, adherens junction, focal adhesion and ribosome. Being one of the common DEG, and highly interactive hub protein in the networks of all the conditions, translationally controlled tumour protein (TPT1) was identified as a significant predictive biomarker for early prognosis and diagnosis of H.pylori induced GC. Therefore, the mechanisms behind TPT1 should be further studied using in vitro cell-based functional assays, to determine its role in the progression of H.pylori induced GC.

Identification and Functional Enrichment Analysis of Differentially Expressed Genes in Osteoarthritis

2020 ◽  
Author(s):  
Chen Xu ◽  
Ling-bing Meng ◽  
Yu Xiao ◽  
Yong Qiu ◽  
Ying-jue Du ◽  
...  
Keyword(s):  
Hydrogen Peroxide ◽  
Differentially Expressed Genes ◽  
Cellular Response ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Set Enrichment Analysis ◽  
Functional Enrichment ◽  
Ppi Network ◽  
Gene Set Enrichment ◽  
Gene Set

Abstract Background Osteoarthritis (OA) is a chronic, progressive, inflammatory, degenerative disease, which has become an osteoarthropathy that seriously affects physical health and quality of life of elderly people. However, the etiology and pathogenesis of OA remains unclear. Therefore, the study purposed to utilize bioinformatics technology to perform identification and functional enrichment analysis of differentially expressed genes in osteoarthritis. Method The main methods of this study consist of access to microarray data (GSE82107 and GSE55235), identification of differently expressed genes (DEGs) by GEO2R between OA and normal synovium samples, enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) by Gene Set Enrichment Analysis (GSEA), construction and analysis of protein-protein interaction (PPI) network, significant module and hub genes. Result A total of 300 DEGs were identified, consisting of 64 up-regulated genes and 11 down-regulated genes in OA samples compared to normal synovium tissues. Gene set enrichment analysis of DEGs provided a comprehensive overview of some major pathophysiological mechanisms in OA: cellular response to hydrogen peroxide, P53 signaling pathway and so on. The study also built the PPI network, and a total of 10 key genes were identified: CYR61, PENK, GOLM1, DUSP1, ATF3, STC2, FOSB, PRSS23, TF, and TNC. Conclusion DEGs exists between OA patients and normal cartilage tissue, which may be involved in the related mechanism of OA development, especially cellular response to hydrogen peroxide and CYR61.

scholarly journals A Novel Three-miRNA Signature Identified Using Bioinformatics Predicts Survival in Esophageal Carcinoma

2020 ◽  
Vol 2020 ◽  
pp. 1-11 ◽  
Author(s):  
KunZhe Wu ◽  
ChunDong Zhang ◽  
Cheng Zhang ◽  
DongQiu Dai
Keyword(s):  
Growth Factor ◽  
Esophageal Carcinoma ◽  
Target Genes ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Rna Seq ◽  
Mirna Signature ◽  
Cox Regression Analysis ◽  
Ppi Networks

Objective. We identified differentially expressed microRNAs (DEMs) between esophageal carcinoma (ESCA) tissues and normal esophageal tissues. We then constructed a novel three-miRNA signature to predict the prognosis of ESCA patients using bioinformatics analysis. Materials and Methods. We combined two microarray profiling datasets from the Gene Expression Omnibus (GEO) database and RNA-seq datasets from the Cancer Genome Atlas (TCGA) database to analyze DEMs in ESCA. The clinical data from 168 ESCA patients were selected from the TCGA database to assess the prognostic role of the DEMs. The TargetScan, miRDB, miRWalk, and DIANA websites were used to predict the miRNA target genes. Functional enrichment analysis was conducted using the Database for Annotation, Visualization, and Integrated Discovery (David), and protein-protein interaction (PPI) networks were obtained using the Search Tool for the Retrieval of Interacting Genes database (STRING). Results. With cut-off criteria of P<0.05 and |log2FC| > 1.0, 33 overlapping DEMs, including 27 upregulated and 6 downregulated miRNAs, were identified from GEO microarray datasets and TCGA RNA-seq count datasets. The Kaplan–Meier survival analysis indicated that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) was significantly associated with the overall survival of ESCA patients. The results of univariate and multivariate Cox regression analysis showed that the three-miRNA signature was a potential prognostic factor in ESCA. Furthermore, the gene functional enrichment analysis revealed that the target genes of the three miRNAs participate in various cancer-related pathways, including viral carcinogenesis, forkhead box O (FoxO), vascular endothelial growth factor (VEGF), human epidermal growth factor receptor 2 (ErbB2), and mammalian target of rapamycin (mTOR) signaling pathways. In the PPI network, three target genes (MAPK1, RB1, and CLTC) with a high degree of connectivity were selected as hub genes. Conclusions. Our results revealed that a three-miRNA signature (miR-1301-3p, miR-431-5p, and miR-769-5p) is a potential novel prognostic biomarker for ESCA.

scholarly journals Identification and Interaction Analysis of Significant Genes and MicroRNAs in Pterygium

2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Siying He ◽  
Hui Sun ◽  
Yifang Huang ◽  
Shiqi Dong ◽  
Chen Qiao ◽  
...  
Keyword(s):  
Differentially Expressed Genes ◽  
Molecular Mechanisms ◽  
Interaction Analysis ◽  
Interaction Network ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Gene Expression Omnibus ◽  
Functional Enrichment ◽  
Differentially Expressed ◽  
Differentially Expressed Mirnas

Purpose. MiRNAs have been widely analyzed in the occurrence and development of many diseases, including pterygium. This study aimed to identify the key genes and miRNAs in pterygium and to explore the underlying molecular mechanisms. Methods. MiRNA expression was initially extracted and pooled by published literature. Microarray data about differentially expressed genes was downloaded from Gene Expression Omnibus (GEO) database and analyzed with the R programming language. Functional and pathway enrichment analyses were performed using the database for Annotation, Visualization and Integrated Discovery (DAVID). The protein-protein interaction network was constructed with the STRING database. The associations between chemicals, differentially expressed miRNAs, and differentially expressed genes were predicted using the online resource. All the networks were constructed using Cytoscape. Results. We found that 35 miRNAs and 301 genes were significantly differentially expressed. Functional enrichment analysis showed that upregulated genes were significantly enriched in extracellular matrix (ECM) organization, while downregulated genes were mainly involved in cell death and apoptotic process. Finally, we concluded the chemical-gene affected network, miRNA-mRNA interacted networks, and significant pathway network. Conclusion. We identified lists of differentially expressed miRNAs and genes and their possible interaction in pterygium. The networks indicated that ECM breakdown and EMT might be two major pathophysiological mechanisms and showed the potential significance of PI3K-Akt signalling pathway. MiR-29b-3p and collagen family (COL4A1 and COL3A1) might be new treatment target in pterygium.

scholarly journals Genome-wide phylogenetic analysis, expression pattern, and transcriptional regulatory network of the pig C/EBP gene family

2020 ◽  
Author(s):  
Chaoxin Zhang ◽  
Tao Wang ◽  
Shengwei Liu ◽  
Bing Zhang ◽  
Xue Li ◽  
...  
Keyword(s):  
Phylogenetic Analysis ◽  
Regulatory Network ◽  
Target Genes ◽  
Transcriptional Regulatory Network ◽  
Expression Patterns ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Functional Enrichment ◽  
Rna Seq ◽  
Group I

Abstract Background: The vertebrate C/EBP transcription factors regulate many important biological processes, such as cell proliferation, differentiation, signal transduction, inflammation, and energy metabolism. The first C/EBP protein was identified in rat liver nuclei. Development of sequencing technology resulted in identification of the C/EBP genes in various species. In this study, a bioinformatics approach was used to determine the distribution of the members of the C/EBP family in vertebrates. A phylogenetic tree was constructed to analyze the C/EBP genes in vertebrates. Based on RNA-seq data, the expression patterns of pig C/EBP members in various tissues were analyzed. In addition, a gene transcription regulatory network was constructed with pig C/EBP members as the core.Results: We identified a total of 92 C/EBP genes in 17 vertebrate genomes. Phylogenetic analysis showed that all C/EBP TFs were classified into two groups; group I contained C/EBPβ TFs, and group II contained the remaining C/EBP TFs. The C/EBPα, C/EBPβ, C/EBPδ, C/EBPγ, and C/EBPζ genes were expressed ubiquitously with inconsistent expression patterns in various tissues. Moreover, a pig C/EBP regulatory network was constructed, including C/EBP genes, TFs, and miRNAs. A total of 39 FFL motifs were detected in the pig C/EBP regulatory network. Based on the RNA-seq data, gene expression patterns related to this FFL sub-network were analyzed in 27 adult Duroc tissues. Certain FFL motifs may be tissue specific. Functional enrichment analysis indicated that C/EBP and its target genes are involved in many important biological pathways. Conclusions: These results provide valuable information that clarifies the evolutionary relationships of the C/EBP family and contributes to the understanding of the biological function of C/EBP genes.

scholarly journals Integrated Analysis of lncRNA and mRNA Reveals Novel Insights into Wool Bending in Zhongwei Goat

Animals ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. 3326
Author(s):  
Xiaobo Li ◽  
Zhanfa Liu ◽  
Shaohui Ye ◽  
Yue Liu ◽  
Qian Chen ◽  
...  
Keyword(s):  
Signaling Pathway ◽  
Target Genes ◽  
Economic Value ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Hair Follicles ◽  
Functional Enrichment ◽  
Integrated Analysis ◽  
Rna Seq ◽  
Camp Signaling Pathway

Chinese Zhongwei goat is a rare and precious fur breed as its lamb fur is a well-known fur product. Wool bending of lamb fur of the Zhongwei goat is its most striking feature. However, the curvature of the wool decreases gradually with growth, which significantly affects its quality and economic value. The mechanism regulating the phenotypic changes of hair bending is still unclear. In the present study, the skin tissues of Zhongwei goats at 45 days (curving wool) and 108 days (slight-curving wool) after birth were taken as the research objects, and the expression profiling of long non-coding RNAs (lncRNAs) and mRNAs were analyzed based on the Ribo Zero RNA sequencing (RNA-seq) method. In total, 46,013 mRNAs and 13,549 lncRNAs were identified, of which 352 were differentially expressed mRNAs and 60 were. lncRNAs. Functional enrichment analysis of the target genes of lncRNAs were mainly enriched in PI3K-Akt, Arachidonic acid metabolic, cAMP, Wnt, and other signaling pathways. The qRT-PCR results of eight selected lncRNAs and target genes were consistent with the sequencing result, which indicated our data were reliable. Through the analysis of the weighted gene co-expression network, 13 co-expression modules were identified. The turquoise module contained a large number of differential expressed lncRNAs, which were mainly enriched in the PI3K-Akt signaling pathway and cAMP signaling pathway. The predicted LOC102172600 and LOC102191729 might affect the development of hair follicles and the curvature of wool by regulating the target genes. Our study provides novel insights into the potential roles of lncRNAs in the regulation of wool bending. In addition, the study offers a theoretical basis for further study of goat wool growth, so as to be a guidance and reference for breeding and improvement in the future.

scholarly journals g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update)

2019 ◽  
Vol 47 (W1) ◽  
pp. W191-W198 ◽  
Author(s):  
Uku Raudvere ◽  
Liis Kolberg ◽  
Ivan Kuzmin ◽  
Tambet Arak ◽  
Priit Adler ◽  
...  
Keyword(s):  
Web Design ◽  
Enrichment Analysis ◽  
Functional Enrichment Analysis ◽  
Biological Data ◽  
Functional Enrichment ◽  
Quality Data ◽  
Primary Data ◽  
Web Interface ◽  
Biological Data Analysis ◽  
Data Source

Abstract Biological data analysis often deals with lists of genes arising from various studies. The g:Profiler toolset is widely used for finding biological categories enriched in gene lists, conversions between gene identifiers and mappings to their orthologs. The mission of g:Profiler is to provide a reliable service based on up-to-date high quality data in a convenient manner across many evidence types, identifier spaces and organisms. g:Profiler relies on Ensembl as a primary data source and follows their quarterly release cycle while updating the other data sources simultaneously. The current update provides a better user experience due to a modern responsive web interface, standardised API and libraries. The results are delivered through an interactive and configurable web design. Results can be downloaded as publication ready visualisations or delimited text files. In the current update we have extended the support to 467 species and strains, including vertebrates, plants, fungi, insects and parasites. By supporting user uploaded custom GMT files, g:Profiler is now capable of analysing data from any organism. All past releases are maintained for reproducibility and transparency. The 2019 update introduces an extensive technical rewrite making the services faster and more flexible. g:Profiler is freely available at https://biit.cs.ut.ee/gprofiler.

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