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Critical evaluation of copy number variant calling methods using DNA methylation |
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| Authors: | Varun Kilaru Anna K. Knight Seyma Katrinli Dawayland Cobb Adriana Lori Charles F. Gillespie Adam X. Maihofer Caroline M. Nievergelt Anne L. Dunlop Karen N. Conneely Alicia K. Smith |
| Affiliation: | 1. Department of Gynecology and Obstetrics, Emory University School of Medicine, Atlanta, Georgia;2. Department of Psychiatry and Behavioral Sciences, Emory University School of Medicine, Atlanta, Georgia;3. Department of Psychiatry, University of California San Diego, San Diego, California;4. Department of Psychiatry, University of California San Diego, San Diego, California Center of Excellence for Stress and Mental Health, Veterans Affairs San Diego Healthcare System, San Diego, California Research Service, Veterans Affairs San Diego Healthcare System, San Diego, California;5. Nell Hodgson Woodruff School of Nursing, Emory University School of Medicine, Atlanta, Georgia Department of Family and Preventive Medicine, Emory University School of Medicine, Atlanta, Georgia;6. Department of Human Genetics, Emory University School of Medicine, Atlanta, Georgia |
| Abstract: | Recent technological and methodological developments have enabled the use of array-based DNA methylation data to call copy number variants (CNVs). ChAMP, Conumee, and cnAnalysis450k are popular methods currently used to call CNVs using methylation data. However, so far, no studies have analyzed the reliability of these methods using real samples. Data from a cohort of individuals with genotype and DNA methylation data generated using the HumanMethylation450 and MethylationEPIC BeadChips were used to assess the consistency between the CNV calls generated by methylation and genotype data. We also took advantage of repeated measures of methylation data collected from the same individuals to compare the reliability of CNVs called by ChAMP, Conumee, and cnAnalysis450k for both the methylation arrays. ChAMP identified more CNVs than Conumee and cnAnalysis450k for both the arrays and, as a consequence, had a higher overlap (~62%) with the calls from the genotype data. However, all methods had relatively low reliability. For the MethylationEPIC array, Conumee had the highest reliability (57.6%), whereas for the HumanMethylation450 array, cnAnalysis450k had the highest reliability (43.0%). Overall, the MethylationEPIC array provided significant gains in reliability for CNV calling over the HumanMethylation450 array but not for overlap with CNVs called using genotype data. |
| Keywords: | ChAMP cnAnalysis450k CNV Conumee DNA methylation |