# Differentiation state prediction

DNA methylation data lacked a general way to quantify differentiation state; EpiDiff trains a random forest on 1,298 differentiation-associated CpGs to output a continuous index from 0 to 1. It reached 0.97 classification accuracy in independent datasets and rose with age in many sorted cell types, underpinned by a developmental epigenetic drift toward the mesoderm lineage.

DNA methylation data lacked a general way to quantify differentiation state; EpiDiff trains a random forest on 1,298 differentiation-associated CpGs to output a continuous index from 0 to 1. It reached 0.97 classification accuracy in independent datasets and rose with age in many sorted cell types, underpinned by a developmental epigenetic drift toward the mesoderm lineage.