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Benchmark Dataset for Somatic Mutation Calling in Cell-Free DNA

This study provides a comprehensive benchmarking resource for somatic variant detection in cell-free DNA (cfDNA) from cancer patients. Longitudinal plasma samples from colorectal and breast cancer cohorts were selected to create patient-matched dilution series spanning ultra-low to high circulating-tumour-DNA (ctDNA) fractions, while preserving each individual’s germline and clonal haematopoiesis background. Deep whole-genome sequencing (150×) and ultra-deep whole-exome sequencing (2,000×) generated a reference call set of ~37,000 single-nucleotide variants and ~58,000 insertions/deletions. These data enabled systematic evaluation of nine somatic variant callers across variable ctDNA levels and sequencing depths, and were further used to explore machine-learning–guided parameter tuning. The resulting dataset offers an openly accessible framework for developers and clinicians to assess and optimize somatic variant calling in liquid biopsy applications.

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Plasma cfDNA DNA samples from healthy people and cancer patients

Please contact Anders Jacobsen Skanderup for data access

Studies are experimental investigations of a particular phenomenon, e.g., case-control studies on a particular trait or cancer research projects reporting matching cancer normal genomes from patients.

Study ID Study Title Study Type
EGAS50000001313 Cancer Genomics
  • Changed dataset title to: Benchmark Dataset for Somatic Mutation Calling in Cell-Free DNA
  • Dataset Released

This table displays only public information pertaining to the files in the dataset. If you wish to access this dataset, please submit a request. If you already have access to these data files, please consult the download documentation.

ID File Type Size Quality Report
Located in
EGAF50000449234 bam 317.4 GB
EGAF50000449235 bam 386.2 GB
EGAF50000449236 bam 171.5 GB
EGAF50000449237 bam 359.8 GB
EGAF50000449238 bam 259.2 GB
EGAF50000449239 bam 180.9 GB
EGAF50000449240 bam 307.6 GB
EGAF50000449241 bam 398.0 GB
EGAF50000449242 bam 171.4 GB
EGAF50000449243 bam 216.6 GB
EGAF50000449244 bam 179.6 GB
EGAF50000449245 bam 215.5 GB
EGAF50000449246 csv 402 Bytes
13 Files (3.2 TB)