CGHnormaliter Package (Version 1.14.0)

This package contains an implementation of the CGHnormaliter strategy for normalization of two-channel array Comparative Genomic Hybridization (aCGH) data displaying many copy number imbalances. The key idea of our method is that temporary exclusion of aberrations from the aCGH data allows for a more appropriate calculation of the LOWESS regression curve. As a result, after normalization, the log2 intensity ratios of the normals will generally be closer to zero and better reflect the biological reality. We coined this normalization strategy ‘local-LOWESS’ since only a subset of the log2 ratios is considered in the LOWESS regression. The strategy can be summarized as follows (see Figure 1). Initially the log2 intensity ratios are segmented using DNAcopy [5]. The segmented data are then given as input to a calling tool named CGHcall [2] to discriminate the normals from gains and losses. These normals are subsequently used for normalization based on LOWESS. These steps are then iterated to refine the normalization. For more detailed information we refer to the publications of the method [4, 3].