Abstract
Aim: We compared predictive modeling approaches to estimate placental methylation using cord blood methylation. Materials & methods: We performed locus-specific methylation prediction using both linear regression and support vector machine models with 174 matched pairs of 450k arrays. Results: At most CpG sites, both approaches gave poor predictions in spite of a misleading improvement in array-wide correlation. CpG islands and gene promoters, but not enhancers, were the genomic contexts where the correlation between measured and predicted placental methylation levels achieved higher values. We provide a list of 714 sites where both models achieved an R2 ≥0.75. Conclusion: The present study indicates the need for caution in interpreting cross-tissue predictions. Few methylation sites can be predicted between cord blood and placenta.
Original language | English |
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Pages (from-to) | 231-240 |
Number of pages | 10 |
Journal | Epigenomics |
Volume | 9 |
Issue number | 3 |
DOIs | |
State | Published - Mar 2017 |
Keywords
- 450k arrays
- DNA methylation
- cord blood
- epigenetics
- methylation prediction
- placenta
- support vector machine