clusterProfiler 4.0: A universal enrichment tool for interpreting omics data

Wu, Tianzhi; Hu, Erqiang; Xu, Shuaimei; Chen, Meijun; Guo, Pingfan; Dai, Zhigang; Feng, Tingze; Zhou, Lang; Tang, Wenli; Zhan, Li; Fu, Xiaocong; Liu, Shanshan; Bo, Xiaochen; Yu, Guangchuang

doi:10.1016/j.xinn.2021.100141

Cited by 5,434 publications

(4,999 citation statements)

References 45 publications

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“…PCaDB has been developed using R Shiny (https://CRAN.R-project.org/package=shiny), which provides an elegant and powerful web framework for building interactive web applications using the R language (https://www.R-project.org/). The major advantage of Shiny is that a lot of R/Bioconductor packages such as limma (35), clusterProfiler (36), Biobase (44), ggplot2 (45), etc. can be used for the advanced bioinformatics analyses and visualization.…”

Section: Methodsmentioning

confidence: 99%

“…A forest plot for the common genes in 3 or more signatures and a data table with the survival analysis result for all the signature genes are generated. Functional enrichment analysis of the signature genes can be performed using the R package clusterProfiler (36). Many pathway/ontology knowledgebases including KEGG (34), Gene Ontology (GO) (37), Reactome (38), Disease Ontology (DO) (39), Network of Cancer Gene (NCG) (40), DisGeNET (41), and Molecular Signatures Database (MSigDB) (42) are leveraged for the functional analysis.…”

Section: Database Content and Usagementioning

confidence: 99%

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PCaDB - a comprehensive and interactive database for transcriptomes from prostate cancer population cohorts

Jia

2021

Preprint

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Prostate cancer (PCa) is a heterogeneous disease with highly variable clinical outcomes which presents enormous challenges in the clinical management. A vast amount of transcriptomics data from large PCa cohorts have been generated, providing extraordinary opportunities for the comprehensive molecular characterization of the PCa disease and development of prognostic signatures to accurately predict the risk of PCa recurrence. The lack of an inclusive collection and standard processing of the public transcriptomics datasets constrains the extensive use of the valuable resources. In this study, we present a user-friendly database, PCaDB, for a comprehensive and interactive analysis and visualization of gene expression profiles from 50 public transcriptomics datasets with 7,231 samples. PCaDB also includes a single-cell RNA-sequencing (scRNAseq) dataset for normal human prostates and 30 published PCa prognostic signatures. The advanced analytical methods equipped in PCaDB would greatly facilitate data mining to understand the heterogeneity of PCa and to develop prognostic signatures and machine learning models for PCa prognosis. PCaDB is publicly available at http://bioinfo.jialab-ucr.org/PCaDB/.

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Section: Methodsmentioning

confidence: 99%

Section: Database Content and Usagementioning

confidence: 99%

PCaDB - a comprehensive and interactive database for transcriptomes from prostate cancer population cohorts

Jia

2021

Preprint

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“…The list of seed and first-order genes (divided into communities by cluster analysis and upand downregulated genes) were extended with known protein interactions from STRING, IntAct (https://www.ebi.ac.uk/intact/), GOnet (https://tools.dice-database.org/Gonet/), Metascape (http://metascape.org), inBio Discover (https://inbio-discover.com/), Enrichr (https://maayanlab.cloud/Enrichr/) or the R package ClusterProfiler 4.0 [16] and examined for their pathway, function or disease enrichment scores. In this study we use the false discovery rate (FDR) corrected p-values.…”

Section: Enrichment Analysismentioning

confidence: 99%

The Protein-Protein Interaction Network of First Episode Psychosis and Schizophrenia Reveals Possible Trigger Factors and New Drug Targets among Intracellular Signal Transduction Pathways and Neurotoxicity Processes

Maes¹,

Plaimas²,

Suratanee³

et al. 2021

Preprint

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There is evidence that schizophrenia is characterized by activation of the immune-inflammatory response (IRS) and compensatory immune-regulatory (CIRS) systems and lowered neuroprotection. Studies performed on antipsychotic-naïve first episode psychosis (AF-FEP) and schizophrenia (FES) patients are important as they may disclose the pathogenesis of the disease. However, the interactome of FEP/FES is not well delineated. The aim of the current study was to delineate the characteristics of the protein-protein interaction (PPI) network of AN-FEP and its transition to FES and the biological functions, pathways, and molecular patterns, which are over-represented in FEP/FES. PPI network analysis shows that FEP and FEP/FES are strongly associated with a response to a bacterium, TNF, NFκB, RELA, SP1, JAK-STAT, death receptor and TLR4 signaling, and tyrosine phosphorylation of STAT proteins. Specific molecular complexes of the peripheral immune response are associated with microglial activation, neuroinflammation and gliogenesis. FEP/FES is accompanied by lowered protection against inflammation in part attributable to dysfunctional miRNA maturation, deficits in neurotrophin/Trk, RTK and Wnt/catenin signaling and adherens junction organization. Lowered neuroprotection due to reduced neurotrophin/Trk and Wnt/catenin signaling, and DISC1 expression and multiple interactions between lowered BDNF, CDH1, CTNNB, and DISC1 expression, increase the vulnerability to the neurotoxic effects of immune products including cytokines and complement factors. All pathways or molecular patterns enriched in the interactome of FEP/FES are directly or indirectly affected by LPS. In summary: FEP appears to be triggered by a biotic stimulus (e.g. Gram-negative bacteria) which may induce neuro-immune toxicity cascades especially when anti-inflammatory and neurotrophic protections are deficient.

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“…It accommodates positional, expression quantitative trait loci (eQTL) and chromatin interaction mappings, and provides gene-based, pathway and tissue enrichment results. We further used a universal enrichment tool to perform enrichment analyses and generating plots 15 .…”

Section: Functional Analysismentioning

confidence: 99%

Genetically determined serum testosterone level and Covid-19 illness level: A mendelian randomization study

Xiong

Miao³

et al. 2021

Preprint

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Background: It is hypothesized that different levels of hormones especially serum testosterone level could explain the sex differences between men and women on the susceptibility and case fatality rate of COVID-19. However, traditional observational studies that support this hypothesis could not effectively establish the causal effects. Objective: Utilizing recently published genome-wide associations studies (GWAS) on serum Testosterone level and on COVID-19 related phenotypes, we sought to assess the causality through Mendelian Randomization (MR) analyses. We further applied a suite of statistical genomics methods to further explore the biological mechanisms. Results: We found that testosterone level is significantly associated with Covid-19 critical illness. All six MR methods yielded significant associations. There is no significant association between Testosterone and COVID-19 respiratory failure or COVID-19 susceptibility. Conclusion: Based on the GWAS currently available, we provide support for a causal role of Testosterone on COVID-19 critical illness. Nevertheless, we recognize that the COVID-19 susceptibility GWAS effort is still ongoing and there is no such strong locus as CCR5 for HIV discovered for COVID-19.

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clusterProfiler 4.0: A universal enrichment tool for interpreting omics data

Cited by 5,434 publications

References 45 publications

PCaDB - a comprehensive and interactive database for transcriptomes from prostate cancer population cohorts

PCaDB - a comprehensive and interactive database for transcriptomes from prostate cancer population cohorts

The Protein-Protein Interaction Network of First Episode Psychosis and Schizophrenia Reveals Possible Trigger Factors and New Drug Targets among Intracellular Signal Transduction Pathways and Neurotoxicity Processes

Genetically determined serum testosterone level and Covid-19 illness level: A mendelian randomization study

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