MSKCC Cancer Genome Characterization Center

Novel normalization algorithms and QA measures for array CGH.

Normalization of arrayCGH data differs from that of expression data in many respects including that: (1) hybridization signals are typically smaller and with higher background due to the excess of non-target labeling products. (2) small changes in copy number may mark biologically significant events, such as single-copy gains or losses that may accompany unbalanced translocations or chromosomal rearrangements. (3) log2 ratios are expected to be highly correlated between probes targeting adjacent regions in the genome. There is no commercial normalization software, which addresses the unique aspects of aCGH data. We have developed and refined novel approaches to aCGH-specific normalization and QA measures based on more than 1000 hybridizations on Agilent cDNA and oligo expression arrays while in development at Dana-Farber, and several hundred hybridizations on oligo aCGH arrays recently at MSKCC.

Complete Methods Description

The following compressed tar archive has all of the necessary R-code to run the gcNormalization algorithm used here at MSKCC.

gcNormRlib.tar.bz2

Sloan-Kettering Institute Memorial Sloan-Kettering Cancer Center