BMC Genomics

Table 2 Correlations (log2 fold change) between Illumina and Affymetrix mouse "target 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% (560)	Quantile	0.936	0.946	0.936	0.941	0.949	0.949	0.946
	Loess	0.940	0.945	0.944	0.944	0.949	0.949	0.954
	Rank	0.941	0.947	0.944	0.945	0.951	0.951	0.953
	vsn	0.940	0.947	0.945	0.947	0.952	0.952	0.953
10% (1125)	Quantile	0.922	0.936	0.920	0.932	0.940	0.944	0.939
	Loess	0.922	0.932	0.925	0.933	0.939	0.943	0.944
	Rank	0.924	0.935	0.925	0.934	0.941	0.944	0.944
	vsn	0.921	0.933	0.926	0.937	0.943	0.946	0.942
25% (2700)	Quantile	0.843	0.875	0.836	0.857	0.893	0.887	0.883
	Loess	0.834	0.868	0.834	0.854	0.888	0.884	0.882
	Rank	0.843	0.874	0.838	0.859	0.894	0.887	0.886
	vsn	0.826	0.860	0.844	0.863	0.897	0.890	0.873
50% (4600)	Quantile	0.760	0.807	0.596	0.730	0.824	0.825	0.816
	Loess	0.746	0.800	0.596	0.725	0.818	0.823	0.813
	Rank	0.759	0.805	0.598	0.731	0.825	0.825	0.817
	vsn	0.724	0.766	0.607	0.728	0.807	0.814	0.780
100% (10018)	Quantile	0.666	0.732	0.289	0.428	0.732	0.739	0.735
	Loess	0.645	0.722	0.285	0.421	0.724	0.735	0.730
	Rank	0.653	0.721	0.286	0.422	0.723	0.731	0.727
	vsn	0.590	0.647	0.280	0.402	0.670	0.674	0.656

The percentages indicate the percentile cut-off for the intensity on both platforms as well as an approximate number of matches (app. N) selected (normalisation-dependent).

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