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Adjustment of genomic waves in signal intensities from whole-genome SNP genotyping platforms
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 tha...
Autores principales: | , , , , , , , , |
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Formato: | Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2008
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2577347/ https://www.ncbi.nlm.nih.gov/pubmed/18784189 http://dx.doi.org/10.1093/nar/gkn556 |
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author | Diskin, Sharon J. Li, Mingyao Hou, Cuiping Yang, Shuzhang Glessner, Joseph Hakonarson, Hakon Bucan, Maja Maris, John M. Wang, Kai |
author_facet | Diskin, Sharon J. Li, Mingyao Hou, Cuiping Yang, Shuzhang Glessner, Joseph Hakonarson, Hakon Bucan, Maja Maris, John M. Wang, Kai |
author_sort | Diskin, Sharon J. |
collection | PubMed |
description | 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. |
format | Text |
id | pubmed-2577347 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2008 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-25773472009-01-22 Adjustment of genomic waves in signal intensities from whole-genome SNP genotyping platforms Diskin, Sharon J. Li, Mingyao Hou, Cuiping Yang, Shuzhang Glessner, Joseph Hakonarson, Hakon Bucan, Maja Maris, John M. Wang, Kai Nucleic Acids Res Methods Online 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. Oxford University Press 2008-11 2008-09-10 /pmc/articles/PMC2577347/ /pubmed/18784189 http://dx.doi.org/10.1093/nar/gkn556 Text en © 2008 The Author(s) http://creativecommons.org/licenses/by-nc/2.0/uk/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Methods Online Diskin, Sharon J. Li, Mingyao Hou, Cuiping Yang, Shuzhang Glessner, Joseph Hakonarson, Hakon Bucan, Maja Maris, John M. Wang, Kai Adjustment of genomic waves in signal intensities from whole-genome SNP genotyping platforms |
title | Adjustment of genomic waves in signal intensities from whole-genome SNP genotyping platforms |
title_full | Adjustment of genomic waves in signal intensities from whole-genome SNP genotyping platforms |
title_fullStr | Adjustment of genomic waves in signal intensities from whole-genome SNP genotyping platforms |
title_full_unstemmed | Adjustment of genomic waves in signal intensities from whole-genome SNP genotyping platforms |
title_short | Adjustment of genomic waves in signal intensities from whole-genome SNP genotyping platforms |
title_sort | adjustment of genomic waves in signal intensities from whole-genome snp genotyping platforms |
topic | Methods Online |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2577347/ https://www.ncbi.nlm.nih.gov/pubmed/18784189 http://dx.doi.org/10.1093/nar/gkn556 |
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