Cell-Free DNA Nucleosome Footprint (Plasma cfDNA Whole-Genome Sequencing)

Deep whole-genome sequencing of plasma cell-free DNA (cfDNA) that established the foundation for fragmentomics, the family of methods now used to detect and localize cancer from liquid biopsy. Snyder and colleagues showed that cfDNA fragmentation is not random: nucleosome-protected positions survive as a genome-wide footprint that reflects the chromatin of the cells the DNA came from, so fragmentation patterns can infer tissue of origin in healthy and pathological states including cancer. The series contains 60 samples: three deeply sequenced healthy references (the pooled CH01 dataset reaches roughly 230-fold genome coverage), five stage IV cancer patients (small cell lung carcinoma, squamous cell lung carcinoma, colorectal adenocarcinoma, hepatocellular carcinoma, and ductal carcinoma in situ of the breast), and 44 additional stage IV samples that received lighter screening coverage. These fragment-size and nucleosome-positioning signals underpin modern MRD approaches that detect residual tumor from cfDNA fragmentation rather than from individual mutations. The S3 files mounted here are a subset: the five processed genome-wide nucleosome-footprint tracks for the deeply-sequenced samples. The full 60-sample series and the raw plasma cfDNA whole-genome reads remain in NCBI GEO under GSE71378 (BioProject PRJNA291063). Published by Snyder et al., Cell, 2016.

Category
Genomics & Bioinformatics
Provider
Snyder, Kircher, Hill, Daza, Shendure (University of Washington)
License
Public (NCBI GEO / SRA)
DOI
10.1016/j.cell.2016.01.029
Hosted on
Amazon S3, bucket scigantic-mrd-liquid-biopsy/cfdna-nucleosome-snyder/, us-east-1
Access
Free and public. No account with the data provider is needed.
Source
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE71378
Data structure and loading code

Fields

GSM (sample)string (GEO sample accession)
sample title / sourcestring (healthy reference | stage IV can
cancer typestring (small cell lung | squamous cell
library prepstring (double-stranded; IH02 is single-
coveragestring (deep reference ~30-230x vs light

Load the data

# api archive: no mount. Load the GEO series metadata, then pull tracks/reads you need.
# pip install GEOparse
import GEOparse
gse = GEOparse.get_GEO("GSE71378", destdir="./geo")
for gsm, s in list(gse.gsms.items())[:10]:
    print(gsm, s.metadata.get("title"), s.metadata.get("source_name_ch1"))

Written for a Scigantic notebook, where /mnt/archive is the mounted dataset.

Analyze this dataset without downloading it

On Scigantic, Cell-Free DNA Nucleosome Footprint (Plasma cfDNA Whole-Genome Sequencing) opens in a hosted JupyterLab notebook with the data already mounted, so you can read files where they are stored instead of copying them first. Each notebook includes an AI assistant that can see the mounted files and write and run analysis code. Open the dataset page to launch a notebook, or browse the full catalog.

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