A machine learning approach to infer DNase1L3 activity from plasma cell-free DNA fragmentomics
This study demonstrates that machine learning models trained on cell-free DNA fragmentomics can accurately infer DNase1L3 activity and identify R206C homozygotes, while also revealing that the resulting aberrant fragmentome represents a stable, time-dependent end-state in homozygotes compared to the transient effects observed in wildtype or heterozygote individuals.