To support the continuous development of GPLEXUS, please cite: GPLEXUS: Enabling Genome-scale Gene Association Network Reconstruction and Analysis for Very Large-scale Expression Data, Nucleic Acids Research, 2013, doi: 10.1093/nar/gkt983.
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GPLEXUS: Genome-scale Gene Association Network Reconstruction and Analysis for very large-scale expression data    
 
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RMA-based Affymetrix data normalization:

Data normalization is an important step before gene association network construction. To assist with data normalization required by the GPLEXUS, user use the following three options to normalize their Affymetrix GeneChip data based on the Robust Multi-array Average (RMA) method (log2 scale is not necessary) :

  • Option1: Use our online normalization tool
  • User needs to upload a zipped file containing the Affymetrix CEL-files to our webserver to perform normalization.




  • Option2: Use "Affy" module in the R package
  • If a user has more than several hundreds of CEL files, we recommend using the "affy" R package to perform data normalization on local computers. Below are steps how to normalize affymetrix data and save it into a TAB-delimited txt file.

    1. Install R environment and "affy" R package;

    2.Run the following scripts:

    library(affy)

    setwd(“/tmp/affymetrix”)

    Data <- ReadAffy()

    eset <- rma(Data)

    write.exprs(eset,file="rma.txt")

    Please note that the affymetrix expression data will be read from and saved into the folder “/tmp/affymetrix/”. User may change it to any other directory where the affymetrix data is located. The normalized the table-delimited expression data file will be saved in “rma.txt”.


  • Option3: Install and run RMA software under windows environment

Funding:

  • This work was supported by National Science Foundation (Grant ABI-0960897) and the Samuel Roberts Noble Foundation.

Contact:

  • To contact us, please write to: bioinfo AT noble DOT org


   Funding by the National Science Foundation    Funding by the Oklahoma Center for the Advancement of Science & Technology    Additional funding by the Samuel Roberts Noble Foundation


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