Tag: clusterProfiler

Notch signaling in thyrocytes is essential for adult thyroid function and mammalian homeostasis

Brent, G. A. Mechanisms of thyroid hormone action. J. Clin. Invest. 9, 3035–3043 (2012). Article  Google Scholar  Iwen, K. A., Oelkrug, R. & Brabant, G. Effects of thyroid hormones on thermogenesis and energy partitioning. J. Mol. Endocrinol. 60, R157–R170 (2018). Article  PubMed  CAS  Google Scholar  Biondi, B. & Wartofsky, L….

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cluster analysis – The enrichWP function is no longer recognized in `comparecluster()` (clusterProfiler R package)

I have been using clusterProfiler for quite a while, specifically the compareCluster() function. I have used enrichKEGG()and enrichWP()for my workflow since January 2023. But now fun = “enrichWP” isn’t recognized in the comparecluster() function. Indeed when checking the R doc, it does now state for the fun argument : One…

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No genes mapped in clusterprofiler gseGO

Hello! I’m having issues generating an adequate geneList for running gseGO in clusterProfiler, using keytype = “GO” Similar issues have been described here: No gene mapped gseGO code is: gse <- gseGO(geneList = gene_List, ont = “ALL”, #ont one of “BP”, “MF”, “CC” or “ALL” OrgDb = OrgDb, minGSSize =…

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No gene can be mapped

Hi When I do my data’s Gene Set Enrichment Analysis with ClusterProfiler using codes of Mohammed Khalfan from website, when I run the following code and got the error message. gse <- gseGO(geneList=gene_list, ont = “ALL”, keyType = “ENSEMBL”, nPerm = 10000, minGSSize = 3, maxGSSize = 800, pvalueCutoff =…

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Randomized phase II study of preoperative afatinib in untreated head and neck cancers: predictive and pharmacodynamic biomarkers of activity

Study objectives and endpoints The main objective consisted in identifying predictive biomarkers of efficacy by exploring correlation between baseline potential biomarkers and radiological and metabolic responses to afatinib. Secondary objectives were to identify potential pharmacodynamic biomarkers, to evaluate the efficacy and safety of afatinib and to assess the metabolic and…

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Potent latency reversal by Tat RNA-containing nanoparticle enables multi-omic analysis of the HIV-1 reservoir

Participants and blood collection A total of n = 23 HIV-1 seropositive individuals on stably suppressive ART were included in this study (Supplementary Table 1). Participants were recruited at Ghent University Hospital. 2/23 individuals are female, 21/23 are male; the limited representation of female individuals in our study is a direct reflection of…

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Bioconductor – clusterProfiler

DOI: 10.18129/B9.bioc.clusterProfiler     This package is for version 3.12 of Bioconductor; for the stable, up-to-date release version, see clusterProfiler. statistical analysis and visualization of functional profiles for genes and gene clusters Bioconductor version: 3.12 This package implements methods to analyze and visualize functional profiles (GO and KEGG) of gene…

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ORA with clusterProfiler

Hello everyone, I am trying to do an enrichment analysis of Arabidopsis data, however I am still wondering how to build it or what to use as a background (universe), could you guide me? I am working with this example. diff_genes <- read_delim(file = “differential_genes.tsv”, delim = “\t”) biomartr::organismBM(organism =…

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removeBatchEffect with non-linear model fit

removeBatchEffect with non-linear model fit 0 @2289c15f Last seen 6 hours ago Germany Hello, I am attempting to use limma’s removeBatchEffect for visualization purposes (heatmat & PCA) while fitting non-linear models (splines) to my expression data in DESeq2. Given that my design is balanced, would this approach work within the…

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HER2 low expression breast cancer subtyping and their correlation with prognosis and immune landscape based on the histone modification related genes

Barzaman, K. et al. Breast cancer: Biology, biomarkers, and treatments. Int. Immunopharmacol. 84, 106535 (2020). Article  CAS  PubMed  Google Scholar  Siegel, R. L., Miller, K. D., Wagle, N. S. & Jemal, A. Cancer statistics, 2023. CA Cancer J. Clin. 73(1), 17–48 (2023). Article  PubMed  Google Scholar  Mueller, C., Haymond, A.,…

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Identification and validation of key miRNAs for colon cancer

Introduction With nearly 2 million new cases and 1 million deaths worldwide in 2020, colorectal cancer is the third-most common cancer and the second leading cause of cancer-related deaths.1 According to data from the US Surveillance, Epidemiology and End Results program and the National Program of Cancer Registries program, the…

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extracting Uniprot IDs for Kegg pathways

extracting Uniprot IDs for Kegg pathways 0 I would like to know if it is possible to extract the UniProt IDs for each of the KEGG pathways for specific organisms. From reading the clusterProfiler documentation, I think the information is all there, I’m just not sure, how one can access…

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How can we use the organism database created by makeorgPackageFromNCBI to KEGG and GO analysis using clusterprofiler package.

How can we use the organism database created by makeorgPackageFromNCBI to KEGG and GO analysis using clusterprofiler package. 0 @3e18707b Last seen 10 hours ago India I have transcriptome data of an inhouse sequenced bacterial genome. I made the database for my bacteria using makeOrgPackageFromNCBI command. How can I use…

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MSL2 ensures biallelic gene expression in mammals

Materials Animals All of the mice were kept in the animal facility of the Max Planck Institute of Immunobiology and Epigenetics. The mice were maintained under specific-pathogen-free conditions, with 2 to 5 mice housed in individually ventilated cages (Techniplast). The cages were equipped with bedding material, nesting material, a paper…

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High-throughput screening of genetic and cellular drivers of syncytium formation induced by the spike protein of SARS-CoV-2

Plasmid construction All the constructs used in this study were generated with standard cloning strategies, including PCR, overlapping PCR, oligo annealing, digestion and ligation. Primers were purchased from Genewiz. The plasmid sequence was verified by Sanger sequencing. The pCAG-spike(D614G)-GFP11-mCherry plasmid was modified from Addgene plasmid 158761. Briefly, GFP11 and mCherry…

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Gene expression profiles separate endometriosis lesion subtypes and indicate a sensitivity of endometrioma to estrogen suppressive treatments through elevated ESR2 expression | BMC Medicine

Cea Soriano L, López-Garcia E, Schulze-Rath R, Garcia Rodríguez LA. Incidence, treatment and recurrence of endometriosis in a UK-based population analysis using data from The Health Improvement Network and the Hospital Episode Statistics database. Eur J Contracept Reprod Health Care. 2017;22(5):334–43. Article  PubMed  Google Scholar  Guo SW. Recurrence of endometriosis…

Continue Reading Gene expression profiles separate endometriosis lesion subtypes and indicate a sensitivity of endometrioma to estrogen suppressive treatments through elevated ESR2 expression | BMC Medicine

Analysis of nucleoporin 107 overexpression

Introduction Lung cancer is one of the most common types of cancer worldwide and the leading cause of cancer death.1 The main category of lung cancer is non-small cell lung cancer, accounting for about 85%, and lung adenocarcinoma, as a kind of non-small cell lung cancer, is the most frequently…

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Elevated stress response marks deeply quiescent reserve cells of gastric chief cells

Generation of inducible H2b-GFP knock-in mice Generation of inducible H2b-GFP knock-in mice was performed by using CRISPR/Cas943. In brief, a mixture containing a sgRosa26-1 crRNA43 (8.7 ng/μl, Fasmac, Japan), a tracrRNA (14.3 ng/μl, Fasmac, Japan), a single strand oligo donor nucleotide (ssODN) composed of 5′ arm, adenovirus splicing acceptor, SV40 pA, TRE3G…

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Intrinsic deletion at 10q23.31, including the PTEN gene locus, is aggravated upon CRISPR-Cas9-mediated genome engineering in HAP1 cells mimicking cancer profiles

Introduction The CRISPR-Cas system is a widely used genome engineering technology because of its simple programmability, versatile scalability, and targeting efficiency (Wang & Doudna, 2023). Although researchers are rapidly developing CRISPR-Cas9 tools, the biggest challenge remains to overcome undesired on- and off-targeting outcomes. Previous studies have reported unintended genomic alterations,…

Continue Reading Intrinsic deletion at 10q23.31, including the PTEN gene locus, is aggravated upon CRISPR-Cas9-mediated genome engineering in HAP1 cells mimicking cancer profiles

GDF11 slows excitatory neuronal senescence and brain ageing by repressing p21

Experimental model and subject details Mice Male ICR mice (Laboratory Animal Center of Zhejiang Academy of Medical Sciences) at age of 3 months (M), 9 M and 36 M, male C57BL/B6 wild‐type (WT) mice (Shanghai Slac Laboratory) at age of 3 M and 10 M, male GDF11-flox mice (GDF11f/f, mice carrying the “floxed” GDF11…

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Predicting missing values splines DESeq2

Hello, I am fitting splines in DESeq2 like so: dds <- DESeqDataSetFromMatrix(countData = counts, colData = coldata, design = ~ ns(age_scaled, df = 3)) Plotting later using the code Mike Love posted elsewhere: dat <- plotCounts(dds, gene, intgroup = c(“age”, “sex”, “genotype”), returnData = TRUE) %>% mutate(logmu = design_mat %*%…

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Ref seq/Gene bank accession to Entrez id for cluster profiler

Ref seq/Gene bank accession to Entrez id for cluster profiler 1 I have a list id of GenBank accession (protein) for different bacterial species (these are non model bacterial species). The next step is to do GSEA for these proteins. I tried to convert GenBank accession to entrez id, But…

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Selecting a subset of MSigDB database for GSEA

Selecting a subset of MSigDB database for GSEA 0 Hi all I am analyzing bulk RNA-seq data with GSEA and MSigDB to identify significantly enriched pathways. I am interested in which signaling pathways are enriched, so I am planning on using “C2: curated gene sets”, its subcollection “CP: Canonical pathways”,…

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Bioconductor – TCGAbiolinks

DOI: 10.18129/B9.bioc.TCGAbiolinks     TCGAbiolinks: An R/Bioconductor package for integrative analysis with GDC data Bioconductor version: Release (3.5) The aim of TCGAbiolinks is : i) facilitate the GDC open-access data retrieval, ii) prepare the data using the appropriate pre-processing strategies, iii) provide the means to carry out different standard analyses…

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Bioconductor – GOSemSim

    This package is for version 3.2 of Bioconductor; for the stable, up-to-date release version, see GOSemSim. GO-terms Semantic Similarity Measures Bioconductor version: 3.2 Implemented five methods proposed by Resnik, Schlicker, Jiang, Lin and Wang respectively for estimating GO semantic similarities. Support many species, including Anopheles, Arabidopsis, Bovine, Canine,…

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Bioconductor – ReactomePA

    This package is for version 2.12 of Bioconductor; for the stable, up-to-date release version, see ReactomePA. Reactome Pathway Analysis Bioconductor version: 2.12 This package provides functions for pathway analysis based on REACTOME pathway database. It will implement enrichment analysis, gene set enrichment analysis and functional modules detection. Author:…

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Bioconductor – AnnotationHub

DOI: 10.18129/B9.bioc.AnnotationHub     Client to access AnnotationHub resources Bioconductor version: Release (3.6) This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, Ensembl) can be…

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Early detection of hepatocellular carcinoma via no end-repair enzymatic methylation sequencing of cell-free DNA and pre-trained neural network | Genome Medicine

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, Bray F. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2021;71(3):209–49. Article  PubMed  Google Scholar  Llovet JM, Kelley RK, Villanueva A, Singal AG, Pikarsky E,…

Continue Reading Early detection of hepatocellular carcinoma via no end-repair enzymatic methylation sequencing of cell-free DNA and pre-trained neural network | Genome Medicine

Expression profiles of circRNAs and biomarkers for COPD

Introduction Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory lung disease featured by airflow obstruction with high prevalence, morbidity, and mortality. It is reported that COPD is the third leading cause of death globally at present, and the incidence of COPD in adults over 40 years is more than…

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Single-cell transcriptomics reveals the brain evolution of web-building spiders

Animals for single-cell sequencing Adult samples of the aerial web-building spider (Hylyphantes graminicola) were collected from Anci district, Langfang, Hebei, China (39° 31.90’ N, 116° 38.15’ E) between September and October 2020. Collected spiders used for brain dissection were housed individually in a glass tube (Φ12 mm × 80 mm) at temperature- and humidity-controlled condition (24–26 °C and 50–60%…

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Epigenetic regulation during cancer transitions across 11 tumour types

Specimen data All samples for MM, OV, BRCA, PDAC, UCEC, CRC, CESC/AD, SKCM and HNSCC, as well as 2 NATs for GBM and 1 NAT for ccRCC were collected with informed consent in concordance with Institutional Review Board (IRB) approval at the School of Medicine at Washington University in St…

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Error in Gviz (actually, rtracklayer)

Error in Gviz (actually, rtracklayer) | IdeogramTrack 0 @25075190 Last seen 7 minutes ago South Korea When I run this code (below) iTrack <- IdeogramTrack(genome = “hg19”, chromosome = “chr2”, name = “”) then I get the error Error: failed to load external entity “http://genome.ucsc.edu/FAQ/FAQreleases” Did someone else encounter this…

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Annotation hub and clusterProfiler errors

Annotation hub and clusterProfiler errors 1 @33343537 Last seen 4 hours ago Norway How can I get AnnotationHub() run? Also, clusterProfiler is not working because I am unable to install HPO.db > ah <- AnnotationHub() **Error in `collect()`: ! Failed to collect lazy table. Caused by error in `db_collect()` >…

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Errors in Functional Enrichment Analysis with Clusterprofiler

Errors in Functional Enrichment Analysis with Clusterprofiler 0 library(clusterProfiler)library(org.Hs.eg.db) library(tidyverse) library(DOSE) library(ReactomePA) library(enrichplot) library(fgsea) library(data.table) library(ggplot2) keytypes(org.Hs.eg.db) res = read.csv(“coex.Csv”) head(res) original_gene_list = res$correlation names(original_gene_list) <- res$gene gene_list<-na.omit(original_gene_list) gene_list = sort(gene_list, decreasing = TRUE) gse <- gseGO(geneList=gene_list, ont =”ALL”, keyType = “ENSEMBL”, minGSSize = 3, maxGSSize = 800, pvalueCutoff =…

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A Bioconductor workflow for processing, evaluating,…

Introduction Proteins are responsible for carrying out a multitude of biological tasks, implementing cellular functionality and determining phenotype. Mass spectrometry (MS)-based expression proteomics allows protein abundance to be quantified and compared between samples. In turn, differential protein abundance can be used to explore how biological systems respond to a perturbation….

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Error creating SPIA data for KEGG Orthology (KO) Database KEGG xml files

Hi all, I’m trying to create a SPIA data file for all 483 xml files for the KEGG Orthology (KO) Database. I’m working with a non-model organism that is not supported by KEGG as it’s own organism, so I have to use the KEGG Orthology (KO) Database instead of a…

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Extracting most significant core enrichment genes after performing GSEA

Extracting most significant core enrichment genes after performing GSEA 0 Dear all, I am trying to extract a list of the 10 most significant leading-edge/core enrichment genes after performing GSEA, and visualizing the gene sets with the highest NES, is there any way to do it? I managed to extract…

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Crohn’s Disease treatment after failure of anti-TNF therapy

Introduction Crohn’s Disease (CD) is a typical group of inflammatory bowel disease, a chronic intestinal disease with an unclear cause that fluctuates between clinical remission and relapse. The disease may affect the entirety of the gastrointestinal tract, frequently manifesting as segmental, asymmetric, and transmural lesions. 21–47% of patients present with…

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Missing Org.hs.eg.db GO Annotations for Uniprot IDs

Missing Org.hs.eg.db GO Annotations for Uniprot IDs 0 I have run into an issue when trying to do GO enrichment using ClusterProfiler in combination with org.hs.eg.db. In this analysis, I am interested in the set of proteins (as labeled by their Uniprot ID) that are found to be differentially abundant…

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Investigation of LGALS2 expression in the TCGA database reveals its clinical relevance in breast cancer immunotherapy and drug resistance

Bray, F., Laversanne, M., Weiderpass, E. & Soerjomataram, I. The ever-increasing importance of cancer as a leading cause of premature death worldwide. Cancer 127, 3029–3030. doi.org/10.1002/cncr.33587 (2021). Article  PubMed  Google Scholar  Xia, C. et al. Cancer statistics in China and United States, 2022: Profiles, trends, and determinants. Chin. Med. J….

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Differential Expression Cutoffs for n = 1

Differential Expression Cutoffs for n = 1 1 @2289c15f Last seen 22 hours ago Germany I have an experimental setup of bulk RNAseq with a control group n = 6, and condition group n = 1. It was impossible to get more than one sample for the condition, it is…

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The mutational signature of hypertrophic cardiomyopathy

Introduction Hypertrophic cardiomyopathy (HCM), characterized by asymmetric hypertrophy of the ventricular wall, is a condition where the heart becomes thickened without a distinct inducement.1,2 Epidemiological investigation shows that the estimated prevalence rate of HCM in the general population is 1:500.3,4 The clinical manifestations vary greatly, with no symptoms and mild…

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GENE ONTOLOGY FOR TOMATO-ITAG4.1 OR 4

Hey there! So I was absolutely having the same issue as you. The assembly/annotation version difference across different tools is horrendous when working with Tomato. You can perform GO enrichment using a custom GO annotation file using the enricher() function from the clusterProfiler package. It takes in TERM2GENE and TERM2NAME…

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Identification and validation of FPR1, FPR2, IL17RA and TLR7 as immunogenic cell death related genes in osteoarthritis

Galluzzi, L. et al. Molecular mechanisms of cell death: Recommendations of the Nomenclature Committee on Cell Death 2018. Cell Death Differ. 25(3), 486–541 (2018). Article  PubMed  PubMed Central  Google Scholar  Garg, A. D. et al. Molecular and translational classifications of DAMPs in immunogenic cell death. Front. Immunol. 6, 588 (2015)….

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Functional analysis of differentially expressed circular RNAs in sheep subcutaneous fat | BMC Genomics

Chikwanha, O. C., P. Vahmani, V. Muchenje, M. E. R. Dugan and C. Mapiye (2018). Nutritional enhancement of sheep meat fatty acid profile for human health and wellbeing. Food research international (Ottawa, Ont.) 104: 25–38. doi.org/10.1016/j.foodres.2017.05.005. Khan R, Raza SHA, Schreurs N, Xiaoyu W, Hongbao W, Ullah I, et al….

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Gene ontology results differ from cite to software?

Gene ontology results differ from cite to software? 1 Hi, I am doing transcriptomic analysis, When I do GO analysis in R with ClusterProfiler package I get the most enriched terms in BP as below; response to alcohol response to metal ion regulation of membrane potential regulation of cytosolic calcium…

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DeSeq2 data comparison and extracting outputs

Hi, I have an RNA-seq experiment where there are 2 conditions and 2 genotypes. I am trying to figure out how to output the 2 conditions with 2 genotypes from the dds object. I have read online resources, however, it is still not clear what is extracted. I followed and…

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Bioconductor – RNASeqR

DOI: 10.18129/B9.bioc.RNASeqR     RNASeqR: an R package for automated two-group RNA-Seq analysis workflow Bioconductor version: Release (3.11) This R package is designed for case-control RNA-Seq analysis (two-group). There are six steps: “RNASeqRParam S4 Object Creation”, “Environment Setup”, “Quality Assessment”, “Reads Alignment & Quantification”, “Gene-level Differential Analyses” and “Functional Analyses”….

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SL-scan identifies synthetic lethal interactions in cancer using metabolic networks

Datasets The gene expression data, mutation data, CRISPR, and drug perturbation data sets used in this study were obtained from the Depmap project depmap.org/portal/download/all/. The gene expression data set consists of the log2 transformed transcript per million (TPM) values of 19,221 protein-coding genes from 1406 cell lines across 33 cancer…

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Ties in reranked list

Ties in reranked list 0 I’m trying to perform GSEA with the fgsea package in R: fgseaRes<-fgsea(pathways=pathwaysH,stats=new_res_important) However, I receive the error: Warning message: In preparePathwaysAndStats(pathways, stats, minSize, maxSize, gseaParam, : There are ties in the preranked stats (5.02% of the list). The order of those tied genes will be…

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Whole exome sequencing and transcriptome analysis in two unrelated patients with novel SET mutations

Moeschler JB, Shevell M, Committee on G. Comprehensive evaluation of the child with intellectual disability or global developmental delays. Pediatrics. 2014;134:e903–18. PubMed  Google Scholar  Patel DR, Cabral MD, Ho A, Merrick J. A clinical primer on intellectual disability. Transl Pediatr. 2020;9:S23–35. PubMed  PubMed Central  Google Scholar  Baker K, Devine RT,…

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Functional characterization of Alzheimer’s disease genetic variants in microglia

Nott, A. et al. Brain cell type-specific enhancer-promoter interactome maps and disease-risk association. Science 366, 1134–1139 (2019). Article  CAS  PubMed  PubMed Central  Google Scholar  Neuner, S. M., Tcw, J. & Goate, A. M. Genetic architecture of Alzheimer’s disease. Neurobiol. Dis. 143, 104976 (2020). Article  CAS  PubMed  PubMed Central  Google Scholar …

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High pvalues when using clusterProfiler for seurat

High pvalues when using clusterProfiler for seurat 0 Hi, I am trying to run clusterProfiler::GSEA version 4.8.3 for each cluster of my SeuratObj When ranking the DEG based on logFC I get decent ES/NES scores however my q/p values are usually > 0.05 sometimes even >0.5. However, when I re-run…

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Transcriptomics Meta-Analysis Reveals Phagosome and Innate Immune System Dysfunction as Potential Mechanisms in the Cortex of Alzheimer’s Disease Mouse Strains

Aken BL, Ayling S, Barrell D, Clarke L, Curwen V, Fairley S et al (2016) The Ensembl gene annotation system. Database (Oxford) baw093 Bagaria J, Nho K, An SSA (2021) Importance of GWAS in finding un-targeted genetic association of sporadic Alzheimer’s disease. Mol Cell Toxicol 17(3):233–244 Article  CAS  Google Scholar …

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Cell-free chromatin immunoprecipitation to detect molecular pathways in heart transplantation

Abstract Existing monitoring approaches in heart transplantation lack the sensitivity to provide deep molecular assessments to guide management, or require endomyocardial biopsy, an invasive and blind procedure that lacks the precision to reliably obtain biopsy samples from diseased sites. This study examined plasma cell-free DNA chromatin immunoprecipitation sequencing (cfChIP-seq) as…

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Revealing mechanism of Methazolamide for treatment of ankylosing spondylitis based on network pharmacology and GSEA

Braun, J. & Sieper, J. Ankylosing spondylitis. Lancet 369, 1379–1390. doi.org/10.1016/S0140-6736(07)60635-7 (2007). Article  PubMed  Google Scholar  Lai, S. W., Kuo, Y. H. & Liao, K. F. Incidence of inflammatory bowel disease in patients with ankylosing spondylitis. Ann. Rheum. Dis. 80, e144. doi.org/10.1136/annrheumdis-2019-216362 (2021). Article  PubMed  Google Scholar  Bukowski, B. R….

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Bioconductor – famat

DOI: 10.18129/B9.bioc.famat   Functional analysis of metabolic and transcriptomic data Bioconductor version: Release (3.17) Famat is made to collect data about lists of genes and metabolites provided by user, and to visualize it through a Shiny app. Information collected is: – Pathways containing some of the user’s genes and metabolites…

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Bioconductor – CeTF

DOI: 10.18129/B9.bioc.CeTF   Coexpression for Transcription Factors using Regulatory Impact Factors and Partial Correlation and Information Theory analysis Bioconductor version: Release (3.17) This package provides the necessary functions for performing the Partial Correlation coefficient with Information Theory (PCIT) (Reverter and Chan 2008) and Regulatory Impact Factors (RIF) (Reverter et al….

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How to load a galaxy DESeq results table into R so i can continue my workflow there

How to load a galaxy DESeq results table into R so i can continue my workflow there 0 Hello i have a DESeq2 results table wich i generated in Galaxy so i download it to R so i can use clusterProfiler and GOseq to do the functional and domain annotation….

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Gene Ontology – How to do Transcript Ontology?

Gene Ontology – How to do Transcript Ontology? 0 Hi all, I am very new and I apologize if I ask very basic and stupid questions. I’ve been kind of thrown into doing transcriptomics and there isn’t anyone in my lab who can teach/help me with this. I have run…

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Top 25 Bioconductor Interview Questions and Answers

Bioconductor is an open-source software project that provides tools for the analysis and comprehension of high-throughput genomic data. It’s a powerful tool, widely used in bioinformatics and computational biology to process and analyze intricate biological data. Bioconductor’s strength lies in its vast array of packages specifically tailored for genomics research,…

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ClusterProfiler EMAP plot – what are the annotations?

ClusterProfiler EMAP plot – what are the annotations? 0 Hi, Using clusterprofiler an generated an emap plot from my enrichment data – would anyone be able to tell me where the grouping terms (bottom right) come from / how they are made? They look potentially like they are just picking…

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Bioconductor – fcoex

DOI: 10.18129/B9.bioc.fcoex   FCBF-based Co-Expression Networks for Single Cells Bioconductor version: Release (3.17) The fcoex package implements an easy-to use interface to co-expression analysis based on the FCBF (Fast Correlation-Based Filter) algorithm. it was implemented especifically to deal with single-cell data. The modules found can be used to redefine cell…

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Integrated unbiased multiomics defines disease-independent placental clusters in common obstetrical syndromes | BMC Medicine

Barker DJ. The origins of the developmental origins theory. J Intern Med. 2007;261:412–7. Article  CAS  PubMed  Google Scholar  Barker DJ, Gluckman PD, Godfrey KM, Harding JE, Owens JA, Robinson JS. Fetal nutrition and cardiovascular disease in adult life. Lancet. 1993;341:938–41. Article  CAS  PubMed  Google Scholar  Cain MA, Salemi JL, Tanner…

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GO annotation in R using library(org.Hs.eg.db)

I have a list of genes of from a transcriptomic analysis that I wanted to annotate with GO terms using R. My dataframe looks like this; Module & Cluster Gene Ensembl_ID Gene_Symbol log2FC_L.C FC_L.C p_L.C q_L.C log2FC_LD.C FC_LD.C p_LD.C q_LD.C M1C1 CXCL10 ENSSSCG00000032474 CXCL10 6.943 123.066 1.41E-72 1.6E-70 6.658 101.007…

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Single-cell transcriptomes reveal a molecular link between diabetic kidney and retinal lesions

Animals The animal experiments were approved by the Institutional Animal Care and Use Committee of Jinling Hospital (Nanjing, China), in accordance with the approved guidelines of the Institutional Animal Care and Use Committee of Jinling Hospital. 7 weeks old male wild-type (wt) and leptin receptor-deficient (db/db) mice on the C57BLKS/J…

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Ensembl site unresponsive in clusterProfiler analyses

Ensembl site unresponsive in clusterProfiler analyses 0 Hi, thanks for all the useful work. I’m writing to ask about an issue I’ve recently encountered with clusterProfiler in its latest version. I’m trying to implement an approach using parallel::mclapply and some clusterProfiler functions (e.g. groupGO, enrichGO, gseGO) to process few sets…

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Multi-omics data provide insight into the adaptation of the glasshouse plant Rheum nobile to the alpine subnival zone

Yang, Y. et al. Advances in the studies of plant diversity and ecological adaptation in the subnival ecosystem of the Qinghai-Tibet plateau. Chin. Sci. Bull. 64, 2856–2864 (2019). Article  Google Scholar  Zhang, Y., Li, B. & Zheng, D. Datasets of the boundary and area of the Tibetan plateau. Acta Geographica…

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Identification, sorting and profiling of functional killer cells via the capture of fluorescent target-cell lysate

Kagi, D., Ledermann, B., Burki, K., Zinkernagel, R. M. & Hengartner, H. Molecular mechanisms of lymphocyte-mediated cytotoxicity and their role in immunological protection and pathogenesis in vivo. Annu. Rev. Immunol. 14, 207–232 (1996). Article  CAS  PubMed  Google Scholar  Prager, I. & Watzl, C. Mechanisms of natural killer cell-mediated cellular cytotoxicity….

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Mycobacterial DNA-binding protein 1 is critical for BCG survival in stressful environments and simultaneously regulates gene expression

Koul, A. et al. Delayed bactericidal response of Mycobacterium tuberculosis to bedaquiline involves remodelling of bacterial metabolism. Nat. Commun. doi.org/10.1038/ncomms4369 (2014). Article  PubMed  Google Scholar  Global Tuberculosis Report 2021. www.who.int/publications/digital/global-tuberculosis-report-2021. Colditz, G. A. et al. Efficacy of BCG vaccine in the prevention of tuberculosis: Meta-analysis of the published literature. JAMA…

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ClusterProfiler GeneRatio demoninator not the same for all values

ClusterProfiler GeneRatio demoninator not the same for all values 0 Hello, I was running clusterprofiler in order to see enriched pathways/modules using the KEGG database. One thing I noticed after running everything and looking at my final data output with the GeneRatio and BgRatio is that the denominator of my…

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Analysis of endoplasmic reticulum stress-related gene signature for the prognosis and pattern in diffuse large B cell lymphoma

Swerdlow, S. H. et al. The 2016 revision of the World Health Organization classification of lymphoid neoplasms. Blood 127, 2375–2390 (2016). Article  CAS  PubMed  PubMed Central  Google Scholar  Sehn, L. H. & Salles, G. Diffuse large B-cell lymphoma. N. Engl. J. Med. 384, 842–858 (2021). Article  CAS  PubMed  PubMed Central …

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Enricher with Gene Symbols

Enricher with Gene Symbols 0 Hi! I have a list of genes with abs(logfc) >= 0.9 like this: > genes [1] “MDM2” “CDK4” “CCND2” “FLNA” “RBP7” “EDNRB” “EPHA4” “PTPRB” “PPP1R13L” “TPM1” “INSR” [12] “DLC1” “WNT7B” “SFRP1” “IFI16” “ZMAT3” “MEST” “AKT3” “CD36” “SRD5A1” “KIF23” “EPOR” So the list has the gene…

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agriGO calculate q-value

agriGO calculate q-value 0 Hi everyone, I have been using agriGOv2 for GO enrichment analysis and the output generates GO term,Ontology,Description,Number in input list,Number in BG/Ref,p-value,FDR. I was wondering if there is a way to get q-value? Paper (www.ncbi.nlm.nih.gov/pmc/articles/PMC2896167/) states that method to calculate q-value with Storey is available. However,…

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Converting gene id to entrez id with clusterprofiler

Converting gene id to entrez id with clusterprofiler 0 Hi, Im new to R and i’ve been trying to use clusterprofiler to convert my gene_ids to entrez_id for further analysis. I work on the msu7 rice genome and my gene ids looks like this (LOC_Os08g09610, LOC_Os06g05660). Since, it was a…

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gseGO() –> No gene can be mapped

Dear all, I have a list of S. cerevisiae genes and I want to do GO enrichment analysis using clusterProfiler. I already obtained some information using enrichGO() and groupGO(), and I want to see what I can obtain with gseGO(). I use the package org.Sc.sgd.db as my organism database. Here…

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Identification of immuno-inflammation-related biomarkers | JIR

Introduction Acute myocardial infarction (AMI) is the sudden irreversible necrosis of heart muscle, which commonly results from atherosclerotic plaque disruption and subsequent interruption of blood flow.1 It is one of the heart diseases with the highest prevalence and incidence and brings enormous health and financial burdens.2 Despite the rapid development…

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What to do if normalization introduces this following artifact?

What to do if normalization introduces this following artifact? 0 Hey, I’m using Seurat on an scRNA-seq dataset with two groups of mice – A and B. All of what I write next is true regardless of whether I’ve used normalized counts from the SCT assay or the normalized counts…

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PhyloVelo enhances transcriptomic velocity field mapping using monotonically expressed genes

Salipante, S. J. & Horwitz, M. S. Phylogenetic fate mapping. Proc. Natl Acad. Sci. USA 103, 5448–5453 (2006). Article  CAS  PubMed  PubMed Central  Google Scholar  Sulston, J. E., Schierenberg, E., White, J. G. & Thomson, J. N. The embryonic cell lineage of the nematode Caenorhabditis elegans. Dev. Biol. 100, 64–119…

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Does the gene universe for enrichGo need to be a list of gene names?

Does the gene universe for enrichGo need to be a list of gene names? 1 Hello, When using the enrichGo does the gene universe need to be a gene list or can it be a named list with logfc? Currently I am doing this: genes <- names(gene_list)[abs(gene_list)> 0.9] go_enrich <-…

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Immune Cell Infiltration and Novel Biomarkers of CAD

Introduction Coronary artery disease (CAD) is a major cause of death and disability worldwide,1 and has been proved to be triggered by the interaction of environmental and genetic risk factors. It is considered to be a systemic, progressive inflammatory disease. The atherosclerotic plaque formed in CAD accumulates chronically in the…

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Optimal Over Representation Analysis DE genes foldFC threshold?

Optimal Over Representation Analysis DE genes foldFC threshold? 0 Regarding Over Representation analysis over identification of DGE genes, firstly I have a set of 1550 genes resulting of RNA Seq. Given this number decided to do ORA instead of GSEA. After choosing ORA, I have to pass to enrichGO a…

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Bioinformatics – Bethesda | Mendeley Careers

Job Description Overall Position Summary and Objectives Under this task order, the contractor will provide support services to satisfy the overall operational objectives. The primary objective is to provide services and deliverables through bioinformatics support services as part of an existing bioinformatics team. Minimum EducationMaster’s Resume Max Pages15 Certifications &…

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Molecular features driving cellular complexity of human brain evolution

King, M. C. & Wilson, A. C. Evolution at two levels in humans and chimpanzees. Science 188, 107–116 (1975). Article  ADS  CAS  PubMed  Google Scholar  Konopka, G. et al. Human-specific transcriptional networks in the brain. Neuron 75, 601–617 (2012). Article  CAS  PubMed  PubMed Central  Google Scholar  Liu, X. et al….

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Integrated analysis of copy number variation-associated lncRNAs identifies candidates contributing to the etiologies of congenital kidney anomalies

Study design We aimed to investigate the potential contribution of lncRNAs to the pathogenicity of CAKUT associated CNVs. 19 recurrent CAKUT-associated CNVs were identified based on clinical researches of congenital anomalies of the kidney and urinary tracts (CAKUT) cases3,4,12,13 (Table 1). We retrieved lncRNAs located within these genomic regions as candidate…

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Bioconductor – rrvgo

DOI: 10.18129/B9.bioc.rrvgo     Reduce + Visualize GO Bioconductor version: Release (3.13) Reduce and visualize lists of Gene Ontology terms by identifying redudance based on semantic similarity. Author: Sergi Sayols [aut, cre] Maintainer: Sergi Sayols <sergisayolspuig at gmail.com> Citation (from within R, enter citation(“rrvgo”)): Installation To install this package, start…

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How to Load a Molecular Signature Database into clusterProfiler gseGO?

How to Load a Molecular Signature Database into clusterProfiler gseGO? 0 I am using gseGO this way: gse <- gseGO(geneList=gene_list, ont =”ALL”, minGSSize = 3, maxGSSize = 800, pvalueCutoff = 0.05, verbose = TRUE, OrgDb = org.Hs.eg.db, pAdjustMethod = “fdr”) Let’s say I want to analyze against a molecular signature…

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interpreting results from pathway analysis

interpreting results from pathway analysis 0 I am performing pathway analysis using results from RNA seq. I am using clusterprofileR from R and using the KEGG pathway. I obtained two sets of results using gseKEGG(geneList = my_gene_list, organism = kegg_organism, nPerm = 50000, minGSSize = 3, maxGSSize = 800, pvalueCutoff…

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correct input for pathway analysis

correct input for pathway analysis 0 I am performing pathway analysis using results from RNA seq. I am using clusterprofileR from R and using the KEGG pathway. I performed two sets of analyses (1) Using the filtered list of top ~400 genes with the highest log2fold change (2) Using the…

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The genome of the glasshouse plant noble rhubarb (Rheum nobile) provides a window into alpine adaptation

Billings, W. Adaptations and origins of alpine plants. Arct. Alp. Res. 6, 129–142 (1974). Article  Google Scholar  Agakhanjanz, O. & Breckle, W. Origin and evolution of the mountain flora in middle Asia and neighbouring mountain regions. in Arctic and Apine Biodiversity: Patterns, Causes and Ecosystem Consequences (eds. Chapin, F. &…

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Gene Set Comparison Without Expression Data

Gene Set Comparison Without Expression Data 1 I have been looking all over the web to find some answers to my problem but unfortunately, I was unsuccessful. I wish to determine whether an a priori defined set of genes in my case genes associated with Epidermolysis bullosa shows statistically significant,…

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Differentially expressed genes in breast cancer

Introduction Breast cancer represents the most frequently diagnosed and fatal malignant neoplasm among women worldwide. In 2020, breast cancer accounted for the fifth-highest rate of cancer death.1 Current data indicates that cancer is both a hereditary and epigenetic disease. Many major aspects of tumor biology are controlled by epigenetic modifications,…

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Failure in installing the ggtree, enrichplot, and ggtree (Bioconductor packages )

Failure in installing the ggtree, enrichplot, and ggtree (Bioconductor packages ) 0 Hello everyone! Yesterday, I tried to install ggtree, enrichplot, and ggtree in my RStudio (verision 4.1.0) but it turned out they couldn’t be successfully installed and a few warning messages popped out, though I had already installed all…

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Response of Fragaria vesca to projected change in temperature, water availability and concentration of CO2 in the atmosphere

Loarie, S. R. et al. The velocity of climate change. Nature 462(7276), 1052–1055 (2009). Article  ADS  CAS  PubMed  Google Scholar  Kremer, A. et al. Long-distance gene flow and adaptation of forest trees to rapid climate change. Ecol. Lett. 15, 378–392 (2012). Article  PubMed  PubMed Central  Google Scholar  IPCC. Climate change…

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could not find function “gseGO” in ClusterProfiler

could not find function “gseGO” in ClusterProfiler 1 I am trying to run the code using the example data set, gse <- gseGO(geneList=gene_list, ont =”ALL”, keyType = “ENSEMBL”, nPerm = 10000, minGSSize = 3, maxGSSize = 800, pvalueCutoff = 0.05, verbose = TRUE, OrgDb = org.Dm.eg.db, pAdjustMethod = “none”) however…

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Extract geneID following GO enrichment analysis

Hello, I have performed GO analysis using enrichGO function provided from Clusterprofiler package used in R. This is my code I used for that as follows: ego = enrichGO(gene = df$REFSEQ, OrgDb = “org.At.tair.db”, keyType = “TAIR”, ont = “ALL”, pAdjustMethod = “BH”, pvalueCutoff = 0.05, qvalueCutoff = 0.05, readable…

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Integration of bulk RNA sequencing data and single-cell RNA sequencing analysis on the heterogeneity in patients with colorectal cancer

Bao X, Shi R, Zhao T, Wang Y, Anastasov N, Rosemann M et al (2021) Integrated analysis of single-cell RNA-seq and bulk RNA-seq unravels tumour heterogeneity plus M2-like tumour-associated macrophage infiltration and aggressiveness in TNBC. Cancer Immunol Immunother 70(1):189–202 Article  CAS  PubMed  Google Scholar  Becht E, McInnes L, Healy J,…

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How to extract genes of a specific GO-term/pathway

clusterprofiler: How to extract genes of a specific GO-term/pathway 2 I was wondering how to get the list of genes grouped in a particular GO-Term of Biological Pathway. I have an enrichGO output (using the clusterprofiler package). From this result, I’ve into a bar plot (see below). For example, my…

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Identification of macrophage-related genes in sepsis-induced ARDS using bioinformatics and machine learning

Screening of differentially expressed genes in GSE32707 According to the screening criteria of differentially expressed genes, there were 489 differentially expressed genes between the control and sepsis groups, of which 152 genes were downregulated in sepsis patients and 337 genes were upregulated in sepsis patients (Fig. 1A). In contrast, there were…

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Establishment of risk model, analysis of immunoinfiltration

Introduction Atrial fibrillation (AF) is a tachyarrhythmia whose incidence and prevalence are steadily increasing with better chronic disease management in the aging global population. As of 2020, 37.5 million patients worldwide were affected by AF, accounting for 0.51% of the global population.1 As a common arrhythmia, AF greatly increases the…

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