GEO series

caArray_jacob-00182: Gene expression-based survival prediction in lung adenocarcinoma: a multi-site, blinded validation study

GSE68465 Homo sapiens (human) Expression microarray 462 samples Submitted 2015/05/02 Platform GPL96

At a glance

Expression microarray · human · 462 samples

What it is: Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism: Homo sapiens (human)
Topic: Lung cancerThis series is part of our curated briefing on it.
Samples: 462 samples
Data you can get: A processed expression table (series matrix) and the array files, from NCBI.

Summary (written by the submitters)

Here we report a large, training*testing, multi-site, blinded validation study to characterize the performance of several prognostic models based on gene expression for 442 lung adenocarcinomas. The hypotheses proposed examined whether microarray measurements of gene expression either alone or combined with basic clinical covariates (stage, age, sex) could be used to predict overall survival in lung cancer subjects.

Read the full summary ↓

Several models examined produced risk scores that substantially correlated with actual subject outcome. Most methods performed better with clinical data, supporting the combined use of clinical and molecular information when building prognostic models for early-stage lung cancer. This study also provides the largest available set of microarray data with extensive pathological and clinical annotation for lung adenocarcinomas.

This dataset

Open GSE68465 in finder → Find more human microarray datasets → Lung cancer landscape →

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 (GSE68465_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: 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 PRJNA282809. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 18641660) ↗

Samples in this study

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+ 462 more — browse all 462 samples with per-sample file links →

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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.