Tag: clusterProfiler

Introduction Kidney cancer is one of the most commonly diagnosed tumors around the globe.1 According to the statistics from the World Health Organization, annually, there are more than 140,000 RCC-related deaths.2 ccRCC is the most typical subtype of kidney cancer and contributes to the majority of kidney cancer-related deaths.3,4 Until…

1. Van den Berge K, Hembach KM, Soneson C, Tiberi S, Clement L, Love MI, Patro R, Robinson MD. RNA sequencing data: Hitchhikers guide to expression analysis. Annu Rev Biomed Data Sci. 2019;2(1):139–73. doi.org/10.1146/annurev-biodatasci-072018-021255. Article  Google Scholar  2. Conesa A, Madrigal P, Tarazona S, Gomez-Cabrero D, Cervera A, McPherson A,…

Introduction Renal cell carcinoma (RCC) accounts for approximately 2–3% of all malignant tumors, and its prevalence is rising. Metastatic RCC accounts for 25–30% of all RCC cases, and has an exceedingly poor prognosis.1 In 2020, among approximately 430,000 newly discovered cases of RCC, 179,000 died.2 Clear cell renal cell carcinoma…

Introduction Alzheimer’s disease (AD) ranks first among the common dementia type of the world. According to epidemiological investigation from the International Alzheimer’s disease association, about 45 million people has been suffered from AD, and the number is expected to increase to 131 million in 2050.1 Despite the widespread prevalence of…

I am not sure what is the proper way to carry out over-representation analysis (and also gene set enrichment analysis) for RNAseq data. Ideally, the analysis can be performed in R, otherwise, if the software/ platform can export the output file (also include all the non-statistical-significant term) will also be…

What is the codification in genestrand 1 and 2? 0 Hi there, I’m doing some peak annotation using ChIPseeker library(ChIPseeker) library(TxDb.Hsapiens.UCSC.hg38.knownGene) library(clusterProfiler) library(annotables) library(org.Hs.eg.db) txdb <- TxDb.Hsapiens.UCSC.hg38.knownGene peaks= readPeakFile(“peaks_”, header = F) peakAnno <- annotatePeak(peaks, tssRegion=c(-3000, 3000), TxDb=txdb, annoDb=”org.Hs.eg.db”) peaks_annot <- as.data.frame(peakAnno) In my annotation file “geneStrand” is codified as…

clusterProfiler won’t read gene list 0 So I have a list of DE genes that I would like to analyse for enriched GO and KEGG terms. I was going to use clusterProfiler for this, but I can’t seem to get past constructing the gene list. I have followed the vignette…

Introduction Coronary artery disease (CAD) is a complex pathology associated with behavioral and environmental factors.1–3 CAD shows high prevalence and is associated with a high fatality rate among cardiovascular diseases. The main manifestations of CAD are stable or unstable angina pectoris and identifiable or unrecognized myocardial infarction.4 The main risk…

DOI: 10.18129/B9.bioc.conclus     ScRNA-seq Workflow CONCLUS – From CONsensus CLUSters To A Meaningful CONCLUSion Bioconductor version: Release (3.13) CONCLUS is a tool for robust clustering and positive marker features selection of single-cell RNA-seq (sc-RNA-seq) datasets. It takes advantage of a consensus clustering approach that greatly simplify sc-RNA-seq data analysis…

clusterProfiler: number of GO terms in results 0 I am working with a non-model organism. So I constructed TERM2GENE and TERM2NAME files and used enricher to run GO enrichment analysis. The code I used was below. Finally, I got 71 GO terms in the result. But actually, there are 99…

Can cnetplot plot points change shape in clusterprofiler? 0 I have a cnetplot and I am wondering if it is possible for me to do further categorising of the plot by point shape? I have a cnetplot of genes and their interacting pathways, but the genes also have a few…

Sorry for lateness, I wanted to do something similar. This is what I did for reference: Using a Seurat generated gene list for input into ClusterProfiler to see the GO or KEGG terms per cluster. I’ll keep the meat and potatoes of the Seurat vignette in this tutorial: library(dplyr) library(Seurat)…

FindMarkers for ClusterProfiler 1 Hi, I recently ran FindMarkers to compare DEG between two different clusters in a single-cell RNA-seq analysis This is my code: markers= FindMarkers(obj, ident.1=c(4), ident.2 = c(5)) head(markers) dim(markers) table(markers$avg_log2FC > 0) table(markers4v5$p_val_adj < 0.05 & markers$avg_log2FC > 0) I would like to run ClusterProfiler to…

working with .gmt files 3 Hi! I have downloaded a pathway data set in .gmt format form the GSEA website. I’m wondering how can I properly read this data set in R. Could anyone help me? Thank you!   myposts • 9.5k views • link updated 2 hours ago by…

I have a cnetplot from running enrichment with kegg using clusterprofiler. I have scores input as the fold change but for each gene in the plot they are not varying in colour to show their difference in the fold change score. My dataset is genes of entrez IDs and then…

What’s the difference between enrichKEGG and gseKEGG 3 Hi, I was wondering what is the difference between enrichKEGG and gseKEGG in R package ClusterProfile. Thanks! clusterprofiler KEGG • 2.3k views Source link

Functional enrichment analysis of bacteria 2 Hello, I have gene lists from an RNA-seq experiment from E.coli bacteria. So far, I have only worked with model organisms, which are supported by biomaRt, so conversion of gene IDs and functional enrichment analysis within R was easy. Now that I am working…