Normalisation / Illumina - lumi pipeline


Normalizes Illumina arrays to remove systematic bias using the lumi method.



This tool normalizes Illumina BeadSummaryData files. Please note that all the samples must be in one file. In addition to the identifier column (preferably ProbeID), the file must contain the following columns for each sample: AVG, BEAD_STDERR, Avg_NBEADS and DetectionPval. The filename must end with ".txt", and you should NOT use the Import tool for bringing the data into Chipster (in the Import files -window change the action to "Import directly").

Note that you have to enter the organism of the sample.

If you have a BeadSummaryData that reports the probe identifiers as Array_Address_Id (for example 4900685) instead of Probe_Id (for example ILMN_2607609), change the setting for the parameter Probe identifier. Please note that processing the data with Array_Address_Id is slower.

Normalization methods include quantile normalization, loess, robust spline normalization (rsn) which combines features of loess and quantile normalizations, and variance stabilizing normalization (vsn).

The default transformation is log2, but you can also select variance stabilizing transformation (vst). You can either skip the background correction (usually BeadStudio output data has already been background corrected), or use the option bgAdjust.affy, which will call the bg.adjust function in affy package.


A tab-delimited text file containing gene names and expression estimates.


This tool uses Bioconductor package lumi. Please cite the article:

Du P, Kibbe WA, Lin SM (2008) lumi: a pipeline for processing Illumina microarray, Bioinformatics, 24, 1547-1548.