Epigenetic Pacemaker: A fast conditional expectation maximization algorithm for modeling epigenetic state
DNA methylation is widely used to model physiological phenotypes, such as aging1 and type II diabetes2. The epigenetic pacemaker, EPM, is an implementation of a fast conditional expectation maximization algorithm used to model epigenetic states associated with a phenotype of interest 3 The EPM was first introduced by Snir et al. 4 as an extension of the Universal Pacemaker (UPM). The EPM can model non-linear epigenetic trait associations directly without transformation of the phenotype of interest5.
pip3 install EpigeneticPacemaker
Please see the tutorial section for usage examples.
- Horvath, S. DNA methylation age of human tissues and cell types. Genome Biol. 14, R115 (2013).
- Orozco, L. D. et al. Epigenome-wide association in adipose tissue from the METSIM cohort. Hum. Mol. Genet. 0, 223495 (2018).
- Snir, S. & Pellegrini, M. An epigenetic pacemaker is detected via a fast conditional expectation maximization algorithm. 10, 695–706 (2018).
- Snir, S., vonHoldt, B. M. & Pellegrini, M. A Statistical Framework to Identify Deviation from Time Linearity in Epigenetic Aging. PLoS Comput. Biol. 12, 1–15 (2016).
- Snir, S., Farrell, C. & Pellegrini, M. Human epigenetic ageing is logarithmic with time across the entire lifespan. Epigenetics (2019). doi:10.1080/15592294.2019.1623634