INVEX—a web-based tool for integrative visualization of expression data

Xia, Jianguo; Lyle, Ngan H.; Mayer, Matthew L.; Pena, Olga M.; Hancock, Robert E. W.

doi:10.1093/bioinformatics/btt562

Cited by 60 publications

(40 citation statements)

References 11 publications

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“…An FDR ≤ 0.001 and an absolute value of log 2 Ratio ≥ 1 (more than 2.0 fold change) were used as thresholds to determine significant differences in gene expression. For microarray experiment, a Student t test with FDR multiple testing correction was applied to the data using the INVEX web 56 . Transcripts with an adjusted P value < 0.05 and an absolute value of log 2 Ratio ≥ 1 (more than 2.0 fold change) in transcript level were considered as significantly differentially expressed.…”

Section: Methodsmentioning

confidence: 99%

Comparative genomic and transcriptional analyses of the carbohydrate-active enzymes and secretomes of phytopathogenic fungi reveal their significant roles during infection and development

Lyu

Shen

Fù

et al. 2015

Sci Rep

103

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Our comparative genomic analysis showed that the numbers of plant cell wall (PCW)- and fungal cell wall (FCW)-degradation-associated carbohydrate-active enzymes (CAZymes) in necrotrophic and hemibiotrophic fungi are significantly larger than that in most biotrophic fungi. However, our transcriptional analyses of CAZyme-encoding genes in Melampsora larici-populina, Puccinia graminis and Sclerotinia sclerotiorum showed that many genes encoding PCW- and FCW-degradation-associated CAZymes were significantly up-regulated during the infection of both necrotrophic fungi and biotrophic fungi, indicating an existence of a universal mechanism underlying PCW degradation and FCW reorganization or modification, which are both intimately involved in necrotrophic and biotrophic fungal infection. Furthermore, our results showed that the FCW reorganization or modification was also related to the fungal development. Additionally, our transcriptional analysis of the secretome of S. sclerotiorum showed that many secreted protein-encoding genes were dramatically induced during infection. Among them, a small, cysteine-rich protein SsCVNH was experimentally confirmed to be essential for the virulence and sclerotial development, indicating that the small secreted proteins might also play crucial roles as potential effectors in host-non-specific necrotrophic fungi.

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Section: Methodsmentioning

confidence: 99%

Comparative genomic and transcriptional analyses of the carbohydrate-active enzymes and secretomes of phytopathogenic fungi reveal their significant roles during infection and development

Lyu

Shen

Fù

et al. 2015

Sci Rep

103

View full text Add to dashboard Cite

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“…The metabolite list can be selected from the results of a previous analysis downloaded from MetaboAnalyst. Similarly, the gene list can be easily obtained using many excellent web-based tools such as GEPAS ( 22 ) or INVEX ( 23 ). After users have uploaded their data, the genes and metabolites are then mapped to KEGG metabolic pathways for over-representation analysis and pathway topology analysis ( 21 ).…”

Section: Introductionmentioning

confidence: 99%

MetaboAnalyst 3.0—making metabolomics more meaningful

et al. 2015

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MetaboAnalyst (www.metaboanalyst.ca) is a web server designed to permit comprehensive metabolomic data analysis, visualization and interpretation. It supports a wide range of complex statistical calculations and high quality graphical rendering functions that require significant computational resources. First introduced in 2009, MetaboAnalyst has experienced more than a 50X growth in user traffic (>50 000 jobs processed each month). In order to keep up with the rapidly increasing computational demands and a growing number of requests to support translational and systems biology applications, we performed a substantial rewrite and major feature upgrade of the server. The result is MetaboAnalyst 3.0. By completely re-implementing the MetaboAnalyst suite using the latest web framework technologies, we have been able substantially improve its performance, capacity and user interactivity. Three new modules have also been added including: (i) a module for biomarker analysis based on the calculation of receiver operating characteristic curves; (ii) a module for sample size estimation and power analysis for improved planning of metabolomics studies and (iii) a module to support integrative pathway analysis for both genes and metabolites. In addition, popular features found in existing modules have been significantly enhanced by upgrading the graphical output, expanding the compound libraries and by adding support for more diverse organisms.

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“…40 We then exploited the differential expression of our candidates using the NetworkAnalyst 3.0 software. [41][42][43] Differentially expressed genes of breast cancer compared to the control samples were identified using EdgeR. 44 The counts were normalized using a trimmed mean of M-values (TMM).…”

Section: Rna-sequencing Transcriptome Reanalysis Of Breast Cancer Smentioning

confidence: 99%

A meta‐analysis of microRNA networks regulated by melatonin in cancer: Portrait of potential candidates for breast cancer treatment

Chuffa

Carvalho

Justulin

et al. 2020

Journal of Pineal Research

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Melatonin is a ubiquitous molecule with a broad spectrum of functions including widespread anti-cancer activities. Identifying how melatonin intervenes in complex molecular signaling at the gene level is essential to guide proper therapies. Using meta-analysis approach, herein we examined the role of melatonin in regulating the expression of 46 microRNAs (miRNAs) and their target genes in breast, oral, gastric, colorectal, and prostate cancers, and glioblastoma. The deregulated miRNA-associated target genes revealed their involvement in the regulation of cellular proliferation, differentiation, apoptosis, senescence, and autophagy. Melatonin changes the expression of miRNA-associated genes in breast, gastric, and oral cancers. These genes are associated with cellular senescence, the hedgehog signaling pathway, cell proliferation, p53 signaling, and the hippo signaling pathway. Conversely, colorectal and prostate cancers as well as glioblastoma and oral carcinoma present a clear pattern of less pronounced changes in the expression of miRNA-associated genes. Most notably, colorectal cancer displayed a unique molecular change in response to melatonin. Considering breast cancer network complexity, we compared the genes found during the meta-analysis with RNA-Seq data from breast cancer-bearing mice treated with melatonin. Mechanistically, melatonin upregulated genes associated with immune responses and apoptotic processes, whereas it downregulated genes involved in cellular aggressiveness/metastasis (eg, mitosis, telomerase activity, and angiogenesis). We further characterized the expression profile of our gene subsets with human breast cancer and found eight upregulated genes and 16 downregulated genes that were appositively correlated with melatonin. Our results pose a multi-dimension network of tumor-associated genes regulated by miRNAs potentially targeted by melatonin.

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INVEX—a web-based tool for integrative visualization of expression data

Cited by 60 publications

References 11 publications

Comparative genomic and transcriptional analyses of the carbohydrate-active enzymes and secretomes of phytopathogenic fungi reveal their significant roles during infection and development

Comparative genomic and transcriptional analyses of the carbohydrate-active enzymes and secretomes of phytopathogenic fungi reveal their significant roles during infection and development

MetaboAnalyst 3.0—making metabolomics more meaningful

A meta‐analysis of microRNA networks regulated by melatonin in cancer: Portrait of potential candidates for breast cancer treatment

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