Tag: GEOquery

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…

Hello Everyone , I am new to microarray dataset . I want to do this similar kind of plotting using this same mentioned dataset for a different gene . GEO ID : GSE76008 I have tried GEO2R script : <h6>#</h6> library(GEOquery) library(limma) library(umap) gset <- getGEO(“GSE76008”, GSEMatrix =TRUE, AnnotGPL=TRUE)[1] fvarLabels(gset)…

Linear Models for Microarray Data Bioconductor version: 2.5 Data analysis, linear models and differential expression for microarray data. Author: Gordon Smyth with contributions from Matthew Ritchie, Jeremy Silver, James Wettenhall, Natalie Thorne, Mette Langaas, Egil Ferkingstad, Marcus Davy, Francois Pepin, Dongseok Choi, Di Wu, Alicia Oshlack, Carolyn de Graaf, Yifang…

Hello everyone, I’ve been having the same question for a while now. I’m also conducting my own analysis of differential expression on a microarray dataset in R. However, the data is different from the results obtained using GEO2R. Here’s my line of code: my_id <- “GSE80178” gse <- getGEO(my_id, GSEMatrix…

Comment: Accounting for Batch effect reduces DEGs drastically by rohitsatyam102 &utrif; 20 I might have missed out one detail which might actually be relevant now that I revisited my code. Previously using old reference genome GRC… Comment: Accounting for Batch effect reduces DEGs drastically by rohitsatyam102 &utrif; 20 I don’t…

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…

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…

DOI: 10.18129/B9.bioc.debCAM   Deconvolution by Convex Analysis of Mixtures Bioconductor version: Release (3.17) An R package for fully unsupervised deconvolution of complex tissues. It provides basic functions to perform unsupervised deconvolution on mixture expression profiles by Convex Analysis of Mixtures (CAM) and some auxiliary functions to help understand the subpopulation-specific…

DOI: 10.18129/B9.bioc.Rnits   This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see Rnits. R Normalization and Inference of Time Series data Bioconductor version: 3.16 R/Bioconductor package for normalization, curve registration and inference in time course gene expression data. Author: Dipen P. Sangurdekar <dipen.sangurdekar at…

DOI: 10.18129/B9.bioc.zFPKM   This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see zFPKM. A suite of functions to facilitate zFPKM transformations Bioconductor version: 3.16 Perform the zFPKM transform on RNA-seq FPKM data. This algorithm is based on the publication by Hart et al., 2013…

microarrayDGE analysis protocol modify 0 Hello, I am trying to perform microarray DGE analysis in R. I am following this protocol: www.costalab.org/wp-content/uploads/2020/11/handout.html I am up to the step of selecting the samples following reading in the data using the GEOquery package. sel <- 1:12 However, the protocol selects the first…

DOI: 10.18129/B9.bioc.MACPET     This package is for version 3.15 of Bioconductor; for the stable, up-to-date release version, see MACPET. Model based analysis for paired-end data Bioconductor version: 3.15 The MACPET package can be used for complete interaction analysis for ChIA-PET data. MACPET reads ChIA-PET data in BAM or SAM…

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 …

Hi, Can someone help me understand the quality control steps. Specifically, I want to know if it filtered the bad probes and what is considered a bad probe? Also I wanted to know what the purpose of the box plots and density plot is? and if you perform quality control…

DOI: 10.18129/B9.bioc.autonomics   Generifying and intuifying cross-platform omics analysis Bioconductor version: Release (3.17) This package offers a generic and intuitive solution for cross-platform omics data analysis. It has functions for import, preprocessing, exploration, contrast analysis and visualization of omics data. It follows a tidy, functional programming paradigm. Author: Aditya Bhagwat…

I’m working for a project using GEO, in order to analyze some gene expression data. The SuperSeries I am referring to is GSE73304, but I found some problems working on the SubSeries GSE73303. I started my analysis Microarray expression dataset and everything was fine. Now I have to investigate the…

Dean, J. & Keshavan, M. The neurobiology of depression: An integrated view. Asian J. Psychiatry 27, 101–111 (2017). Article  Google Scholar  Ng, M. et al. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: A systematic analysis for the Global Burden of Disease Study…

Introduction As the leading cause of maternal mortality in early pregnancy, ectopic pregnancy (EP) is responsible for 4–10% of all pregnancy-related deaths,1 but drugs can only be used to treat early EP. However, significant differences in the effects on fertility between surgical treatment and medical treatment have been reported in…

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…

Hunter, D. J. & Bierma-Zeinstra, S. Osteoarthritis. Lancet 393, 1745–1759 (2019). Article  CAS  PubMed  Google Scholar  Puig-Junoy, J. & Ruiz Zamora, A. Socio-economic costs of osteoarthritis: A systematic review of cost-of-illness studies. Semin. Arthritis Rheum. 44, 531–541 (2015). Article  PubMed  Google Scholar  Hunter, D. J., March, L. & Chew, M….

DOI: 10.18129/B9.bioc.GenomicOZone   This package is for version 3.16 of Bioconductor; for the stable, up-to-date release version, see GenomicOZone. Delineate outstanding genomic zones of differential gene activity Bioconductor version: 3.16 The package clusters gene activity along chromosome into zones, detects differential zones as outstanding, and visualizes maps of outstanding zones…

Download Geo Tar File Automatically From Linux/Unix 3 Just a note that the GEOquery bioconductor package does this for a living, if you happen to be targeting R for further processing/analysis. See the help for getGEOSuppFiles() and getGEO(). wget -r -nH –cut-dirs=3 ftp.ncbi.nlm.nih.gov/geo/series/GSE39nnn/GSE39977/ The -r option in the wget command…

illuminaHumanv2.db returning NA for all Illumina probe ID to gene symbol conversion 0 I have downloaded a miRNA expression dataset from NCBI GEO (GSE25631) to study differential gene expression and perform other analyses. As mentioned in GEO, this profiling was performed on GPL8179 Illumina Human v2 MicroRNA expression beadchip. Accordingly,…

This question was also asked on Biostars I am trying to download and analyze a miRNA expression dataset from NCBI GEO (GSE25631). I specifically want non-normalized data to perform normalization and my own set of other analyses later on. Accordingly, I downloaded the Series Matrix File (to match the Sample…

I am trying to download and analyze a miRNA expression dataset from NCBI GEO (GSE25631). I specifically want non-normalized data to perform normalization and my own set of other analyses later on. Accordingly, I downloaded the Series Matrix File (to match the Sample IDs with their phenotype) and the non-normalized…

GEOquery is a software tool developed to access the Gene Expression Omnibus (GEO) directly from BioConductor, an open-source project built in the R statistical programming environment for analyzing and comprehending genomic data. GEOquery eliminates the formatting and parsing problems that have made analyzing GEO data labor-intensive in the past, establishing…

    This package is for version 2.9 of Bioconductor; for the stable, up-to-date release version, see GEOquery. Get data from NCBI Gene Expression Omnibus (GEO) Bioconductor version: 2.9 The NCBI Gene Expression Omnibus (GEO) is a public repository of microarray data. Given the rich and varied nature of this…

I’m working on an R script that downloads gene expression data from GEO, through Bioconductor and the getGEO() function. These commands download all the 436 samples of the repository, but I’m only interested in 157 of them. Precisely, I’m interested in handling only the “samples collection:ch1” column with values “”on…

updating annotation of illumina human methylation 450k data 0 I have managed to create a GenomicRatioSet (minfi object) from an expression set (pulled from GEO using GEOquery) which contains a matrix of pre-processed beta values obtained with the exprs() function as such: GRset <- makeGenomicRatioSetFromMatrix(exprs(Eset), rownames = rownames(exprs(Eset)), pData =…

Hunter, D. J. & Bierma-Zeinstra, S. Osteoarthritis. Lancet 393, 1745–1759 (2019). Article  CAS  Google Scholar  Hunter, D. J., March, L. & Chew, M. Osteoarthritis in 2020 and beyond: A Lancet Commission. Lancet 396, 1711–1712 (2020). Article  Google Scholar  Puig-Junoy, J. & RuizZamora, A. Socio-economic costs of osteoarthritis: A systematic review…

I am looking to analyse some pre-processed infinium 450k methylation data (GSE65820) – values have been normalised and undergone QC and removal of batch effects. I have used GEOquery to download the series matrix file GSE65820 <- getGEO(“GSE65820”, GSEMatrix=TRUE) From this I have extracted metadata about the samples using the…

Lozano, R. et al. Global and regional mortality from 235 causes of death for 20 age groups in 1990 and 2010: a systematic analysis for the Global Burden of Disease Study 2010. Lancet 380(9859), 2095–2128 (2012). Google Scholar  Blachier, M., Leleu, H., Peck-Radosavljevic, M., Valla, D. C. & Roudot-Thoraval, F….

microarray analysis – gene upregulation/downregulation 0 Hi guys, I have performed microarray differential expression analysis using the following R commands/script: library(“arrayQualityMetrics”) > library(GEOquery) > library(oligo) > library(Biobase) > library(affy) > library(“splitstackshape”) > library(“tidyr”) > library(dplyr) > celFiles <- list.celfiles() > affyRaw <- read.celfiles(celFiles) Platform design info loaded. Reading in :…

Hi, I have found that my selected gene, probe I.D 201667_at is differentially expressed between WDLPS and DDLPS tumour tissue samples after performing microarray DEG analysis. Instead of just a p value in a table format: Probe I.D “201667_at” logFC 10.8205874181535 AveExpr 10.6925705768407 t 82.8808890739766 P.Value 3.10189446528995e-88 adj.P Val 3.10189446528995e-88…

Introduction Stroke is one of the leading causes of death and disability worldwide, which causes substantial economic and social burdens.1 Ischemic stroke is caused by insufficient blood and oxygen supply to the brain,2 accounting for about 85% of the casualties of stroke patients.3 The concept of treatment for ischemic injury…

I have installed DESeq2 version 1.36.0 samples <- colnames(txi$counts) group <- as.factor(c(“control”,”control”,”control”,”control”,”control”,”diet”,”diet”,”diet”,”diet”,”diet”, “control”,”control”,”control”,”control”,”control”,”diet”,”diet”,”diet”,”diet”,”diet”,”diet”)) coldata <- data.frame(samples, group, stringsAsFactors = F) coldata <- coldata[,c(“samples”,”group”)] coldata$samples <- factor(coldata$samples) coldata$group <- factor(coldata$group) rownames(coldata) <- sub(“fb”, “”, rownames(coldata)) all(rownames(coldata$samples) %in% colnames(txi)) all(rownames(coldata) == colnames(txi)) TRUE library(DESeq2) ddsTxi <- DESeqDataSetFromTximport(txi, colData = coldata, design =…

GPL arguments in getGEO() 0 Hi, I’ve been trying to get GEO data using the getGEO() function and I was wondering what do the arguments AnnotGPL and getGPL do exactly? I tried setting them to T or F and then comparing the output but I don’t observe any differences, am…

R error : Error in getEAWP(object) : data object isn’t of a recognized data class 0 I get this error in microarray analysis > fit = lmFit(DataSeries, design) Error in getEAWP(object) : data object isn’t of a recognized data class microarray GEOquery • 41 views Login before adding your answer….

R error: unable to find an inherited method for function ‘exprs’ for signature ‘”list”’ 1 Hi I get this error in exprs >DataSeries = getGEO(“GSE5847”, GSEMatrix = T, AnnotGPL = T, destdir = “D:/Microarray Data/sharifi.data” ) >expressionData = exprs(DataSeries) >Error in (function (classes, fdef, mtable) : unable to find an…

How to get data from GEO by using getGEO function ? 0 Hello everyone, I am using R package GEOquery to get a geo object from file ( in my directory) by getgeo function. I already download the required packages BiocManager::install(“DESeq2”) BiocManager::install(“limma”) BiocManager::install(“GEOquery”) library(DESeq2) library(limma) library(Biobase) library(GEOquery) I used this…

Anyone know why I’m not getting ENSG ids for some of these symbols? The example below retrieves `NA` for multiple symbols, including AAED1 [whose ENSG is ENSG00000158122][1]. “` > library(AnnotationHub) > library(org.Hs.eg.db) > library(GEOquery) > temp download.file(getGEO(“GSM4430459″)@header$supplementary_file_1,temp) > genes unlink(temp) > ensids = mapIds(org.Hs.eg.db, keys=genes, column=”ENSEMBL”, keytype=”SYMBOL”, multiVals=”first”) > ensids[“AAED1”]…