There is a link on that page that says "Export table in Tab-delimited format". Click this to save the data as a text file on your computer. You can read this file into a data.frame in R using read.delim().

https://intro2r.com/importing-data.html

I'm not sure if you want to read the .idat files that can be downloaded from the url you shared, or if you want to access ArrayExpress Microarray Database at EBI.

• I think this is how to read the .idat files in R after individually downloading them (the file path is just an example):

if (!requireNamespace("BiocManager", quietly = TRUE)){

install.packages("BiocManager")

}

BiocManager::install("illuminaio")

require("illuminaio")

file

http://web.mit.edu/~r/current/arch/i386_linux26/lib/R/library/limma/html/read.idat.html

Dear Roshan Naik you can download data from website and save all your files in folder called "data" in your C using the following codes.

url

The read.idat function in the limma package will read the idat files directly into an expression object.

Here is the r code:

library(limma)

library(illumination)

read.idat("5154922010_A_Grn.idat", bgxfile, dateinfo = FALSE, annotation = "Symbol", tolerance = 0L, verbose = TRUE)

Retrieve that list of GEO accession and sample types

for ex:

Sample sample_type

GSM123444 Control

GSM123445 treatment1

GSM123456 treatment2

GSM123457 treatment3

GSM123458 treatment4

store the above list in a text file ex "pheno.csv"

Download all .cel microarray data and all the .cel files should be in the same directory where you store "pheno.csv".

Thn load it in R

#setwd() to directory containing CEL files and pheno.csv

## Step 1- Load packages affy and limma

library(affy)

library(limma)

library(gplots)

## Step 2 - Import phenotype data file with CEL file_names and variable_names

pheno

Manuel R. Popp I am interested in accessing the microarray data from the EBI database for analysis of lean vs obese gene expression datasets. The attached images are the output received after entering commands (that you provided) in R studio. But I am unable to see any gene ID or make sense of this output. Kindly guide me.