ArticleScientific reports2015
MeSiC: A Model-Based Method for Estimating 5 mC Levels at Single-CpG Resolution from MeDIP-seq.
Article in Scientific reports, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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Who cites it
9 citing papers in PubMed.
- Current and Emerging Technologies for the Analysis of the Genome-Wide and Locus-Specific DNA Methylation Patterns.Advances in experimental medicine and biology · 2022Article
- Molecular mechanisms of ferroptosis and the potential therapeutic targets of ferroptosis signaling pathways for glioblastoma.Frontiers in pharmacology · 2022Review
- The therapeutic potential of natural products for treating pancreatic cancer.Frontiers in pharmacology · 2022Review
- Ferroptosis in lymphoma: Emerging mechanisms and a novel therapeutic approach.Frontiers in genetics · 2022Review
- Large-scale DNA demethylation occurs in proliferating ovarian granulosa cells during mouse follicular development.Communications biology · 2021Article
- DeepH&M: Estimating single-CpG hydroxymethylation and methylation levels from enrichment and restriction enzyme sequencing methods.Science advances · 2020Article
- Detecting the long non‑coding RNA signature related to spinal cord ependymal tumor subtype using a genome‑wide methylome analysis approach.Molecular medicine reports · 2019Article
- Developmental features of DNA methylation in CpG islands of human gametes and preimplantation embryos.Experimental and therapeutic medicine · 2019Article
- QSEA-modelling of genome-wide DNA methylation from sequencing enrichment experiments.Nucleic acids research · 2017Article
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12 authors.
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Abstract
As the fifth base in mammalian genome, 5-methylcytosine (5 mC) is essential for many biological processes including normal development and disease. Methylated DNA immunoprecipitation sequencing (MeDIP-seq), which uses anti-5 mC antibodies to enrich for methylated fraction of the genome, is widely used to investigate methylome at a resolution of 100-500 bp. Considering the CpG density-dependent bias and limited resolution of MeDIP-seq, we developed a Random Forest Regression (RFR) model method, MeSiC, to estimate DNA methylation levels at single-base resolution. MeSiC integrated MeDIP-seq signals of CpG sites and their surrounding neighbors as well as genomic features to construct genomic element-dependent RFR models. In the H1 cell line, a high correlation was observed between MeSiC predictions and actual 5 mC levels. Meanwhile, MeSiC enabled to calibrate CpG density-dependent bias of MeDIP-seq signals. Importantly, we found that MeSiC models constructed in the H1 cell line could be used to accurately predict DNA methylation levels for other cell types. Comparisons with methylCRF and MEDIPS showed that MeSiC achieved comparable and even better performance. These demonstrate that MeSiC can provide accurate estimations of 5 mC levels at single-CpG resolution using MeDIP-seq data alone.
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