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Integrating methylome and transcriptome signatures expands the molecular classification of the pituitary tumors [RNA-seq]

GSE209903 Homo sapiens (human) DNA methylation 65 samples Submitted 2023/01/26 Platform GPL24676
At a glance

DNA methylation · human · 65 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
65 samples
Data you can get
A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Summary (written by the submitters)
Pituitary tumors (PitNETs) tumorigenesis is still not completely understood. Few studies have integrated exome, methylome, and transcriptome analyses. Taking advantage of a comprehensive phenotypic characterized Brazilian cohort, which has heterogeneous ethnic origin, we combined methylome and transcriptome analysis of the three major subtypes of surgically resectable PitNETs. Here, we included RNA-seq and basal patient / tumor data of 65 PitNETs: GH-secreting (acromegaly,n = 15), ACTH-secreting (Cushing disease, n = 7), and Non-Functioning (n = 43 PitNETs).
This dataset
Download · which file do I need?

Direct links to NCBI and ENA, 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.

2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE209903_RAW.tar (it can run to tens of gigabytes).

3 · Start from the raw reads

Raw sequencing reads

The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.

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

Also filed as BioProject PRJNA862905 and SRA study SRP388415. Searching any of these in the dataset finder brings you back here.

Samples in this study

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