Agilent Two Color Arrays Normalization Results

Input parameters

In this first section of the results page you will find a reminder of the parameters or settings you have used to run the analysis.

Result Files

In this section of the results page you will find normalized data files.

After Agilent two colors normalization procedures three results files are created. These files are text files tab delimited.

Normalized Data File: the M-values file.

Contains the processed intensity measurements for all arrays in the dataset and for all biological features in the arrays. In the two color arrays, with some additional transformation, this is the log ratio of the two channel intensityes: the M-vaues.

Babelomics tries to identify non biological features and to exclude them from all steps of the analysis. If we succeeded in finding out the non biological features of your arrays they will not be represented in the normalized data. If we cannot distinguish non biological spots, all the features will be used in the normalization and reported in the normalized data file.

In this file:

  • Arrays or samples are arranged in columns.
  • Genes, spots or features are set in rows.
  • Some header lines may be included at the beginning of the file. They will all start by #.
  • One of those header lines, starting by #NAMES will contain the names of the arrays in your dataset.
  • The first column contains feature identifiers. For Agilent one color arrays, Babelomics tries to figure out which is the best feature id among those provided within the raw data files. Some other feature ids will we reported in the Feature Data File.

Feature Data File:

The rows in this file match the rows in the normalized data file. The columns, contain some additional array design information about the features in the data you have normalized.

Generally reported feature characteristics are:

  • Any feature ID we find in the raw data files.
  • Any gene or transcript ID we find in the raw data files.
  • Row and Column position of the features within the array layout.
  • Chromosomal position of the target genes or transcripts of each feature in the array (when this information is available within the raw data)

A-values File

For each spot in the two channel arrays, its A-value is defined as the mean of the two color intensities in the log2 scale.

This values are reported by Babelomics in a file which lay out and organization are the same as the M-values ones.


In this section you will find some plots representing the normalized data. You can use them to asses how good the normalization process performed in your dataset. Generally you may compare different normalization options between them using this plots. Also you may want to compare the plots of the normalized data to those of the raw data and check if noise levels are lowered down after normalization. Tools for raw data visualization and assessment can be found in the Utilities Menu.

  • Box-Plots representing the normalized intensity distribution for each of the samples (arrays). In general you want overall distributions across arrays to be very similar after normalization. And as normalized measurements are scaled log ratios you will expect your data to be centered around zero.
  • MA-Plots representing the normalized intensity distribution of each sample against a consensus mean sample. A LOESS line fitting the trend between M and A values is drawn in red. After normalization you expect no trend in the LOESS line, that is, you expect it to be as close as possible tho the horizontal 0 axis.
  • Pseudo Image Plots: represent the normalized intensity of each spot within the array coordinates, creating a pseudo photo of the normalized array. High intensities are represented in red colors, low intensities are represented in blue colors. Ideally you will see an evenly colored image, meaning that, after normalization, there is no spatial effect in the array measurements. M-values ie. log ratios of the two channel intensities are represented in this plots.

Other actions

In this section you will find some links that will take you to further analysis steps proposed by Babelomics.

These steps are often required after normalization and that is the reason why there is a quick link to them. You do not have to follow them necessarily if you do not intend to do such analysis. Moreover, there will be many other analyses that can be done trough the general Babelomics menu but will not be linked here.