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Molecular Classification of Ependymal Tumors across All CNS Compartments, Histopathological Grades, and Age Groups.

GSE65362 Homo sapiens (human) DNA methylation 562 samples Submitted 2015/05/21 Platform GPL13534
At a glance

DNA methylation · human · 562 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
562 samples: 306 distinct titles, 94 of them repeatedGroups 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)
Ependymal tumors across age groups are currently classified and graded solely by histopathology. It is, however, commonly accepted that this classification scheme has limited clinical utility based on its lack of reproducibility in predicting patients' outcome. We aimed at establishing a uniform molecular classification using DNA methylation profiling.
Read the full summary ↓
Nine molecular subgroups were identified in a large cohort of 500 tumors, 3 in each anatomical compartment of the CNS, spine, posterior fossa, supratentorial. Two supratentorial subgroups are characterized by prototypic fusion genes involving RELA and YAP1, respectively. Regarding clinical associations, the molecular classification proposed herein outperforms the current histopathological classification and thus might serve as a basis for the next World Health Organization classification of CNS tumors.
This dataset
Open GSE65362 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 (GSE65362_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 PRJNA273777. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 25965575) ↗
Study design
306 distinct titles, 94 of them repeated
Brain tumor 9305651005_R04C ×2 Brain tumor 9305651003_R02C ×2 Brain tumor 9305651013_R02C ×2 Brain tumor 9533774106_R05C ×2 Brain tumor 9533774101_R06C ×2 Brain tumor 9769100071_R03C ×2 Brain tumor 9533774101_R02C ×2 Brain tumor 9533774107_R03C ×2 +86 more

How we read this: Read from the first 400 of 562 sample titles: 306 distinct titles with little repetition. 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

+ 522 more — browse all 562 samples with per-sample file links →

Datasets on a similar topic

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