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Table 3 Correlation (log2 fold change) between Illumina and Affymetrix mouse Ensembl gene matches for selected normalisations.

From: Comparative analysis of methods for gene transcription profiling data derived from different microarray technologies in rat and mouse models of diabetes

   Affymetrix normalisations
Filter (app. N) Illumina normalisations Scale – Avgdiff Quantile-median polish MAS 5.0 Li-Wong RMA GC-RMA vsn
5% (400) Quantile 0.942 0.949 0.937 0.944 0.951 0.945 0.953
  Loess 0.948 0.950 0.946 0.948 0.952 0.948 0.959
  Rank 0.947 0.951 0.944 0.947 0.953 0.948 0.959
  vsn 0.949 0.954 0.947 0.948 0.957 0.951 0.961
10% (900) Quantile 0.928 0.938 0.922 0.935 0.947 0.947 0.942
  Loess 0.930 0.936 0.928 0.937 0.946 0.947 0.947
  Rank 0.930 0.937 0.927 0.937 0.947 0.948 0.946
  vsn 0.928 0.935 0.927 0.935 0.946 0.946 0.944
25% (2600) Quantile 0.864 0.885 0.867 0.869 0.898 0.896 0.894
  Loess 0.860 0.881 0.869 0.866 0.895 0.894 0.895
  Rank 0.865 0.884 0.870 0.869 0.898 0.897 0.896
  vsn 0.858 0.880 0.876 0.874 0.905 0.904 0.892
50% (15600) Quantile 0.781 0.820 0.689 0.766 0.826 0.825 0.829
  Loess 0.772 0.815 0.688 0.760 0.821 0.822 0.828
  Rank 0.781 0.819 0.691 0.766 0.826 0.825 0.830
  vsn 0.758 0.796 0.695 0.768 0.822 0.819 0.809
100% (14242) Quantile 0.662 0.724 0.284 0.417 0.712 0.722 0.727
  Loess 0.646 0.718 0.280 0.407 0.704 0.718 0.723
  Rank 0.650 0.715 0.280 0.410 0.704 0.714 0.720
  vsn 0.595 0.652 0.275 0.397 0.660 0.666 0.659
  1. The percentages indicate the percentile cut-off for the intensity on both platforms as well as an approximate number of matches (app. N) selected. This number is normalisation-dependent.