Tag: RMA

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using RMA normalized microarray in Limma 0 Hi, i downloaded raw.tar file containing .CEL microarray data from GEO database. and then i use affy() package in R to extracted .CEL file and normalized with RMA(). Can i use this expression data to put in Limma? or it is better to…

DOI: 10.18129/B9.bioc.prebs     Probe region expression estimation for RNA-seq data for improved microarray comparability Bioconductor version: Release (3.5) The prebs package aims at making RNA-sequencing (RNA-seq) data more comparable to microarray data. The comparability is achieved by summarizing sequencing-based expressions of probe regions using a modified version of RMA…

Introduction Chemoresistance is a major challenge for breast cancer treatment.1 The mechanisms of chemoresistance are complex because of crosstalk between receptor tyrosine kinases and downstream pathways, deregulation of cell-cycle and apoptosis regulators, and modulation of tumor-infiltrating immune cells.2 The ATP-binding cassette (ABC) superfamily is one of the largest families of…

I am trying to create orchard plots for a meta-analysis following this guide (daniel1noble.github.io/orchaRd/), when I arrive at the moment of creating the plot with the following code: soil_MA <- rma.mv(yi = ES, V = vES, mods = ~ soil, random = ~1 | code, data = DTW_data) res_soil <-…

RMA with Affymetrix Expression Console vs Oligo package 1 I have 192 .CEL files (chip: Affymetrix Human Clariom S HT ). If I apply the RMA using Affymetrix Expression Console software (Analysis: Gene Level – SST-RMA) or with the rma() function from the Oligo package in R Bioconductor, I get…

South Korea’s Hanwha Defense, after recently clinching a multi-billion dollar contract to supply Australia with 129 AS21 Redback Infantry Fighting Vehicles (IFVs), has disclosed to EurAsian Times that several European and Middle Eastern countries have expressed their interest in the ‘REDBACK.’ The company is one of South Korea’s major defense…

Normalization for microarrays >1000+ samples? 0 Hi all, I am trying to normalize microarray data starting from CEL files of 1000+ patients. It is The Affymetrix HTA 2.0 array. On my cluster it currently only works in about 350 patient batches, but the normalization doesn’t look good because it goes…

affy expression array data 0 Hi, everyone I use the oligo package to read cel files, and use the rma function to transformed them into expression matrix, but what I got was a set of Na value. When I used box plot to visualize the data, it showed nothing, but…

I am performing a meta analysis based on 10 different data sets (derived from different platforms and technologies (RNAseq as well as Microarray)). DGE analysis was pretty much straight forward and mostly performed using limma package. The experimental setup was nothing special, just a treatment (heat) vs. control design. So…

Sung H, Ferlay J, Siegel RL, Laversanne M, Soerjomataram I, Jemal A, et al. 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. doi.org/10.3322/caac.21660. Article  PubMed  Google Scholar  Khan MA, Hakeem AR, Scott N, Saunders RN. Significance…

How to assess quality of publicly available microarray data 0 Hello everyone, I am relatively new to microarray technology and gene expression analysis. I am using publicly available microarray data and I want to know if the data is quality enough for a larger analysis I am doing. I read…

Hello, I would like your suggestions for this error with rma() function, for analysing microRNA-affymetrix data. I downloaded the package cdf (miRNA-4_0-st-v1_CDF) (provided below), created the package with make.cdf.package, installed it with R CMD INSTALL. library(makecdfenv) make.cdf.package(filename = “miRNA-4_0-st-v1.cdf”, packagename = “miRNA-4_0-st-v1.cdf”, cdf.path = “./miRNA_4_0_CDF/”, package.path= “/shared/home/mkondili/Tools_Packages/”, compress = FALSE,…

Martin JA, Hamilton BE, Osterman MJK, Driscoll AK. Births: Final Data for 2018. Natl Vital Stat Rep. 2019;68:1–47. PubMed  Google Scholar  Liu L, Oza S, Hogan D, Chu Y, Perin J, Zhu J, et al. Global, regional, and national causes of under-5 mortality in 2000–15: an updated systematic analysis with…

Normalization of Batch effect removal 1 I am attempting to do an integrated analysis of microarray data. The normalization of each data set is disparate, quantile norm, z-socre, and RMA. Is it still possible to integrate and analyze them with ComBat? ComBat • 65 views Yes, and other packages: While…

Pre-processing for Agilent microarray data? 0 Hi, is there any recommended pre-processing for Agilent microarray data? I know there’re frma and rma for Affymetrix microarray data, but I am not sure about Agilent. I found a R package called AgiMicroRna but it seems to focus on processing data for analysis…

Best tool for trimming and filtering nanopore direct RNA sequencing. 1 Hello, I am new to analyzing long read data. I am trying to create a pipeline for analyzing data from Oxford Nanopore’s MinION Mk1b using the R.9.4.1 flow cell and using the Direct RNA Sequencing Kit. We used only…

normalized input data for GAGE (R) – log-transformed or not? 2 Does GAGE package in R require log-transformed normalized expression values or “just” normalized expression values as an input? gage R microarray gene set analysis • 2.2k views • link updated 2 hours ago by Rob • 0 • written…

Batch effects and what to do about them 0 I’m trying to limit batch effects when combining two microarray experiments that were run on similar but perhaps slightly different versions of the Affymetrix U133A array. I want to use this combined dataset as a test dataset for a gene signature…

I’ve downloaded the CEL files from GSE154619 and want to run a DE test for multiple contrasts. In essence, this data has two treatments(drug vs control) in two tissues. Here’s my code: suppressPackageStartupMessages({ library(affy) library(oligo) library(limma) library(pd.clariom.s.mouse) library(clariomsmousetranscriptcluster.db) library(biomaRt) }) data_dir <- ‘./data/DpQ/GSE154619/’ metadata <- data.frame( treatment = factor(ifelse(grepl(‘DQ’, all_files),…

RMA Normalization & Units 0 I’m working on doing some analysis of drug response in cell lines, specifically the genomics of drug sensitivity in cancer (GDSC). In downloading from the source (www.cancerrxgene.org/gdsc1000/GDSC1000_WebResources/Home.html) the expression data is described as “RMA normalised basal expression profiles for all the cell-lines.” Most of my…

Error in getCdfInfo(object) : 1 @bca66a4b Last seen 1 hour ago Japan Hi I wanted to do a rma analysis for a affymetrix microarray data. but I got a problem. Code should be placed in three backticks as shown below setwd(“~/Downloads/GSE24184_RAW/”) library(affy) library(makecdfenv) data = ReadAffy() data and I got…

gene filtering for agilent microarray using Limma 1 Hello everyone, I’m analysing agilent microarray data using limma package. I want to do gene filter to remove the probes that do not give any expression values. Is there any workflow to filter genes in limma package? Thank you in advance. agilent…

GROMACS version: 2022.3GROMACS modification: NoHere post your question I am trying to run a simulation with two nodes enabling GPU-GPU direct communication. Howver, it is not running as expected and is throwing me the following error. Any help would be appreciated. 🙂 GROMACS – gmx mdrun, 2022.3 (-: Executable: /cvmfs/soft.computecanada.ca/easybuild/software/2020/avx512/MPI/gcc9/cuda11.4/openmpi4/gromacs/2022.3/bin/gmx_mpiData…

Cell culture and treatments Bladder cancer cells lines RT4, MGHU3, RT112, KU19-19, JMSU1, T24 and TCCSup were grown in RPMI-1640 medium (Life Technologies, Carlsbad, CA, USA), supplemented with 10% Fetal Bovine Serum (FBS; Eurobio, Courtaboeuf, France). Normal human urothelium (NHU) cells were from Jennifer Southgate (University of York, UK). NHU were…

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…

Experimental design and processing steps For the EpiSCOPE study [20], DHA supplementation and gender were balanced as much as possible across the 12 450K BeadChips on each glass slide, with these factors also randomly distributed over the 6 rows and 2 columns of 31 slides (Additional file 1: Fig. S1). Blood…

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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…

RMA on different disease labels 0 I’m working with HGU133Plus2 datasets, and I’m determining the best normalization procedures. RMA seems to be the standard in literature, however some papers have been opting away from global normalization procedures: www.nature.com/articles/s41598-020-72664-6 ieeexplore.ieee.org/document/6999142 I’m not familiar with how the statistics with RMA works. So…

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Hi Caitlin, For this study, the uploaded data is normalised via GC-RMA, but is not log [base 2] (log2) transformed. To retrieve it, you need to do: library(GEOquery) gset <- getGEO(‘GSE12657’, GSEMatrix = TRUE, getGPL= FALSE) if (length(gset) > 1) idx <- grep(‘GPL8300’, attr(gset, ‘names’)) else idx <- 1 gset…

[last update: January 27, 2020] igraph allows you to generate a graph object and search for communities (clusters or modules) of related nodes / vertices. igraph is utilised in the R implementation of the popular Phenograph cluster and community detection algorithm (used in scRNA-seq and mass cytometry), and also in…

Sample code for GSE79404 #!/usr/bin/Rscript # general config baseDir <- ‘GSE79404/’ bgxfile <- ‘Annot/HumanHT-12_V4_0_R2_15002873_B.bgx’ targetsfile <- ‘targets.txt’ setwd(baseDir) options(scipen = 99) require(limma) require(RColorBrewer) require(PCAtools) # read in the data and convert the data to an EListRaw object, which is a data object for single channel data x <- read.table(paste0(baseDir, ‘raw/GSE79404_non-normalized.txt’),…

    This package is for version 2.9 of Bioconductor; for the stable, up-to-date release version, see xps. Processing and Analysis of Affymetrix Oligonucleotide Arrays including Exon Arrays, Whole Genome Arrays and Plate Arrays Bioconductor version: 2.9 The package handles pre-processing, normalization, filtering and analysis of Affymetrix GeneChip expression arrays,…

I was thinking about creating a tutorial on how to do a simple microarray analysis in Bioconductor. But, I realized this has already been done quite nicely at the Bioinformatics Knowledgeblog. Their first tutorial on the subject covers installation of necessary packages, downloading of cel files, describing the experiment, loading…

Transcriptome Analysis Console (TAC) VS Oligo package in bioconductor 0 I’m a beginner at processing microarray data. I have 114 CEL files (chip: GeneChip™ miRNA 4.0 Array). I tried the following 2 ways to get the signal values and the output is different with no consistent direction. 1.Transcriptome Analysis Console…

Microarray data normalization 1 Dear all, Sorry for such a basic question, but I got confused. As far as I know, the RMA method implemented in affy package is a standard method for microarray data normalization. Could you let me know if the main code data.rma.norm = rma(raw.data) normalize data…

Clariom-D array – subsetting probes to known genes prior to normalization 0 I am analyzing Clariom-D array data using the oligo package in R. I find that the rma normalization step using all probesets works reasonably well (normalized intensity boxplots centered and evenly distributed), but upon filtering the results only…

Hi all，I met a very strange error when reading and doing RMA of the raw cel files. When i use the following codes to do the background correction and normalization of GSE18997 (platform GPL570), I found the order of some probe IDs of the final results seems to be different…