A benchmark of DNA methylation deconvolution methods for tumoral fraction estimation using DecoNFlow

In cancer patients, circulating cell-free DNA (cfDNA) originates from both healthy and cancer cells, and the proportion of tumor-derived cfDNA serves as a surrogate marker of tumor burden. Tumoral cfDNA can be identified using patient-specific mutations or more general tumor-specific DNA methylation patterns that are preserved in cfDNA, enabling non-invasive cancer detection and monitoring. Accurately estimating tumor fractions remains challenging due to the heterogeneous mixture of cfDNA sources in body fluids. Computational DNA methylation deconvolution methods can address this by estimating tumoral fraction with or without reference methylomes. Here, we benchmarked 10 reference-based and 2 reference-free DNAm deconvolution tools and provide the data generated for this benchmarking, consisting of 10 neuroblastoma cell lines and one healthy cfDNA sample (pooled from 15 healthy cfDNA samples), profiled using cfRRBS.

Type: Epigenetics
Archiver: European Genome-Phenome Archive (EGA)

1 Dataset

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Dataset ID	Description	Technology	Samples
EGAD50000002199	This dataset comprises nine neuroblastoma cell lines used to construct the reference matrix for the RRBS-CL dataset in the corresponding benchmarking study. In addition, it includes one extra neuroblastoma cell line and a pooled cfDNA sample from multiple donors, which were used to generate the in silico mixtures. All the samples were profiled using DNA methylation sequencing.	Illumina NovaSeq 6000	11