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Unsupervised detection of fragment length signatures of circulating tumor DNA using non-negative matrix factorization

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Sequencing of cell-free DNA (cfDNA) is currently being used to detect cancer by searching both for mutational and non-mutational alterations. Recent work has shown that the length distribution of cfDNA fragments from a cancer patient can inform tumor load and type. Here, we propose non-negative matrix factorization (NMF) of fragment length distributions as a novel and completely unsupervised method for studying fragment length patterns in cfDNA. Using shallow whole-genome sequencing (sWGS) of cfDNA from a cohort of patients with metastatic castration-resistant prostate cancer (mCRPC), we demonstrate how NMF accurately infers the true tumor fragment length distribution as an NMF component - and that the sample weights of this component correlate with ctDNA levels (r=0.75). We further demonstrate how using several NMF components enables accurate cancer detection on data from various early stage cancers (AUC = 0.96). Finally, we show that NMF, when applied across genomic regions, can be used to discover fragment length signatures associated with open chromatin.

Original languageEnglish
Article numbere71569
Number of pages15
Publication statusPublished - Jul 2022

Bibliographical note

© 2022, Renaud et al.

    Research areas

  • Biomarkers, Tumor/genetics, Cell-Free Nucleic Acids, Circulating Tumor DNA/genetics, Genomics/methods, Humans, Male, Mutation

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