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Expression profiles of cell populations purified from human CRC (4 ways)

GSE39396 Homo sapiens (human) Expression microarray 24 samples Submitted 2013/01/17 Platform GPL13158
At a glance

Expression microarray · human · 24 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Homo sapiens (human)
Topic
Colorectal cancerThis series is part of our curated briefing on it.
Samples
24 samples: 24 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
The survival of isolated metastatic cells and expansion into macroscopic tumour has been recognized as a limiting step for metastasis formation in several cancer types yet the determinants of this process remain largely uncharacterized. In colorectal cancer (CRC), we identify a transcriptional programme in tumour-associated stromal cells, which is intimately linked to a high risk of developing recurrent disease after therapy.
Read the full summary ↓
A large proportion of CRCs display mutational inactivation of the TGF-beta pathway but paradoxically they are characterized by high TGF-beta production. In these tumours, TGF-beta instructs a transcriptional programme in stromal cells, which confers a high risk of developing metastatic disease. We purified by FACS CD31(+), CD45(+), FAP(+) and Epcam(+) populations from fresh CRC samples and assessed their gene expression profiles
This dataset
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.

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 (GSE39396_RAW.tar), including the raw array or instrument files. Can be large; the picker in step 2 takes just the samples you need.

What the files usually look like: For arrays the series matrix is normally the normalised expression table you want; the raw array files (CEL and similar) are in the RAW.tar.

Also filed as BioProject PRJNA170774. Searching any of these in the dataset finder brings you back here.

Study design
24 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 24 sample titles: 24 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
More Colorectal cancer datasets

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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.