GEO series

A genome-wide DNA methylation-based classifier differentiates intrahepatic cholangiocarcinomas from hepatic metastases of pancreatic ductal adenocarcinoma

GSE217384 Homo sapiens (human) DNA methylation 72 samples Submitted 2023/06/05 Platform GPL21145

At a glance

DNA methylation · human · 72 samples

What it is: DNA methylationChemical marks on DNA that help switch genes on or off.
Organism: Homo sapiens (human)
Samples: 72 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

Differentiating intrahepatic cholangiocarcinomas (iCCA) from hepatic metastases of pancreatic ductal adenocarcinoma (PAAD) is difficult. We hypothesized that DNA-methylation based machine-learning algorithms may be able to perform this task. We assembled genome-wide DNA-methylation data for iCCA, PAAD, and normal bile from publicly available sources. We used an internal cohort consisting of 72 samples to test our classifier.

This dataset

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Download · which file do I need?

Direct links to NCBI, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.

1 · Just have a look

Processed table

The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.

Series matrix ↓

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need.

All supplementary files ↗

3 · The original raw files

Whole study · RAW.tar

Everything the authors deposited as one archive (GSE217384_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

Whole study · RAW.tar ↓

What the files usually look like: Look for beta-value tables or raw IDAT files among the supplementary files.

Also filed as BioProject PRJNA898779. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 37348162) ↗

Samples in this study

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+ 72 more — browse all 72 samples with per-sample file links →

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