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Figure 4 | BMC Bioinformatics

Figure 4

From: Kernel density weighted loess normalization improves the performance of detection within asymmetrical data

Figure 4

MA plots for invariant set based normalization methods using data without the empty genes. (a) Data are background-corrected with GCRMA and normalized at the probe level with KDL. Median polish is used to summarize the probe set expression level. (b) The same as (a) while replacing the normalization with KDQ. (c) Data are background-corrected with GCRMA and normalized at the probe level with quantile. Median polish is used to summarize the probe set expression level. The data are then normalized again at the post summary level with GRSN. (d) Li and Wong's dChip method implemented in R.

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BMC Bioinformatics

ISSN: 1471-2105

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