Methyl-IT:  R package based on signal detection and machine learning

Methyl-IT is a R package based on signal detection and machine learning. Methylation analysis is confronted in Methyl-IT as a signal detection problem, and the method was designed to discriminate methylation regulatory signal from background noise induced by Brownian motion and thermal fluctuations. Our group has proposed an information thermodynamics approach to investigate genome-wide methylation patterning based on the statistical mechanical effect of methylation on DNA molecules (1-3). The information thermodynamics-based approach is postulated to provide greater sensitivity for resolving true signal from the thermodynamic background within the methylome (1).

References

1. Sanchez, R.; Yang, X.; Maher, T.; Mackenzie, S.A. Discrimination of DNA Methylation Signal from Background Variation for Clinical Diagnostics. Int. J. Mol. Sci. 2019, 20, 5343.

2. Sanchez R, Mackenzie SA: Genome-Wide Discriminatory Information Patterns of Cytosine DNA Methylation. Int. J. Mol. Sci. 2016, 17(6), 938.

3. Sanchez R, Mackenzie SA: Information Thermodynamics of Cytosine DNA Methylation. Plos One 2016, 11.

4. Sanchez R, Mackenzie SA: Integrative Network Analysis of Differentially Methylated and Expressed Genes for Biomarker Identification in Leukemia. Sci Rep 2020, 10(1), 2123.

5. Yang, X, Sanchez, R et al.: Segregation of an MSH1 RNAi transgene produces heritable non-genetic memory in association with methylome reprogramming. Nature Communications 2020, 11(1), 2214.