PMCCPMCCPMCC

Search tips
Search criteria 

Advanced

 
Logo of bmcgenoBioMed Centralsearchsubmit a manuscriptregisterthis articleBMC Genomics
 
BMC Genomics. 2009; 10: 401.
Published online Aug 26, 2009. doi:  10.1186/1471-2164-10-401
PMCID: PMC2748095
CGHnormaliter: an iterative strategy to enhance normalization of array CGH data with imbalanced aberrations
Bart PP van Houte,1 Thomas W Binsl,1 Hannes Hettling,1 Walter Pirovano,1 and Jaap Heringacorresponding author1
1Centre for Integrative Bioinformatics VU (IBIVU), VU University Amsterdam, De Boelelaan 1081A, 1081 HV Amsterdam, the Netherlands
corresponding authorCorresponding author.
Bart PP van Houte: bvhoute/at/few.vu.nl; Thomas W Binsl: tbinsl/at/few.vu.nl; Hannes Hettling: hettling/at/few.vu.nl; Walter Pirovano: pirovano/at/few.vu.nl; Jaap Heringa: heringa/at/few.vu.nl
Received September 5, 2008; Accepted August 26, 2009.
Abstract
Background
Array comparative genomic hybridization (aCGH) is a popular technique for detection of genomic copy number imbalances. These play a critical role in the onset of various types of cancer. In the analysis of aCGH data, normalization is deemed a critical pre-processing step. In general, aCGH normalization approaches are similar to those used for gene expression data, albeit both data-types differ inherently. A particular problem with aCGH data is that imbalanced copy numbers lead to improper normalization using conventional methods.
Results
In this study we present a novel method, called CGHnormaliter, which addresses this issue by means of an iterative normalization procedure. First, provisory balanced copy numbers are identified and subsequently used for normalization. These two steps are then iterated to refine the normalization. We tested our method on three well-studied tumor-related aCGH datasets with experimentally confirmed copy numbers. Results were compared to a conventional normalization approach and two more recent state-of-the-art aCGH normalization strategies. Our findings show that, compared to these three methods, CGHnormaliter yields a higher specificity and precision in terms of identifying the 'true' copy numbers.
Conclusion
We demonstrate that the normalization of aCGH data can be significantly enhanced using an iterative procedure that effectively eliminates the effect of imbalanced copy numbers. This also leads to a more reliable assessment of aberrations. An R-package containing the implementation of CGHnormaliter is available at http://www.ibi.vu.nl/programs/cghnormaliterwww.
Articles from BMC Genomics are provided here courtesy of
BioMed Central