Abstract
Whole-genome microarrays with large-insert clones designed to determine DNA copy number often show variation in hybridization intensity that is related to the genomic position of the clones. We found these 'genomic waves' to be present in Illumina and Affymetrix SNP genotyping arrays, confirming that they are not platform-specific. The causes of genomic waves are not well-understood, and they may prevent accurate inference of copy number variations (CNVs). By measuring DNA concentration for 1444 samples and by genotyping the same sample multiple times with varying DNA quantity, we demonstrated that DNA quantity correlates with the magnitude of waves. We further showed that wavy signal patterns correlate best with GC content, among multiple genomic features considered. To measure the magnitude of waves, we proposed a GC-wave factor (GCWF) measure, which is a reliable predictor of DNA quantity (correlation coefficient = 0.994 based on samples with serial dilution). Finally, we developed a computational approach by fitting regression models with GC content included as a predictor variable, and we show that this approach improves the accuracy of CNV detection. With the wide application of whole-genome SNP genotyping techniques, our wave adjustment method will be important for taking full advantage of genotyped samples for CNV analysis.
MeSH Terms
Artifacts
Cell Line
Computational Biology/methods
DNA/analysis
Genetic Variation
Genomics/methods
Genotype
Humans
Oligonucleotide Array Sequence Analysis/methods
Polymorphism, Single Nucleotide
Authors & Affiliations
9 authors, click to expand affiliations / ORCID
Diskin Sharon J
Center for Childhood Cancer Research, Children's Hospital of Philadelphia, Philadelphia, PA 19104, USA.
Li Mingyao
Hou Cuiping
Yang Shuzhang
Glessner Joseph
Hakonarson Hakon
Bucan Maja
Maris John M
Wang Kai
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