Integrative cfDNA profiling from low-pass whole-genome sequencing enables tissue-of-origin prediction in cancer
This stacked ensemble machine learning classifier that integrates 11 multidimensional cfDNA features spanning genomic, fragmentomic, methylation/repeat, and microbial signals provides a robust and non-invasive approach for accurate cancer type identification and has the potential to support clinical decision-making.