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DNA methylation data from CNS-PNETs and various other brain tumor samples

GSE73801 Homo sapiens (human) DNA methylation 593 samples Submitted 2016/02/25 Platform GPL13534
At a glance

DNA methylation · human · 593 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
593 samples: 8 conditions, mostly with about 323 replicates eachGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed table (series matrix) and supplementary files from NCBI.
Summary (written by the submitters)
Primitive neuroectodermal tumours of the central nervous system (CNS PNETs) are highly aggressive, poorly differentiated embryonal tumours occurring predominantly in young children. Using DNA methylation and gene expression profiling we have demonstrated that a significant proportion of institutionally diagnosed CNS PNETs display molecular profiles indistinguishable from those of various other well defined CNS tumour entities, facilitating diagnosis and appropiate therapy for children with these tumours.
Read the full summary ↓
From the remaining fraction of CNS PNETs, we have identified four distinct new CNS tumour entities extending to other neuroepithelial tumours, each associated with a recurrent genetic alteration and particular histopathological and clinical features. These molecular entities, designated “CNS Neuroblastoma with FOXR2 activation (CNS NB FOXR2)”, “CNS Ewing sarcoma family tumour with CIC alteration (CNS EFT CIC)”, “CNS high grade neuroepithelial tumour with MN1 alteration (CNS HGNET MN1)”, and “CNS high grade neuroepithelial tumour with BCOR alteration (CNS HGNET BCOR)”, will enable meaningful clinical trials and the development of therapeutic strategies for patients affected by these poorly differentiated CNS tumours.
This dataset
Open GSE73801 in finder → Find more human methylation datasets →
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 (GSE73801_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 PRJNA297934. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 26919435) ↗
Study design
8 conditions, mostly with about 323 replicates each
dkfz_CNS-PNET_15 ×323 dkfz_EPN_15 ×17 dkfz_HGG_15 ×14 dkfz_ATRT_15 ×12 dkfz_ETMR_15 ×10 dkfz_EWS_15 ×9 dkfz_CPC_15 ×8 dkfz_DIG_15 ×7

Supports a between-group comparison across 400 samples.

How we read this: 8 replicated groups read from the first 400 of 593 sample titles; they account for 400 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.

Samples in this study

+ 553 more — browse all 593 samples with per-sample file links →

Datasets on a similar topic

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Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.