BMC Genomics

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

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.

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