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The landscape of pharmacogenomic interactions in human cancer

GSE68379 Homo sapiens (human) DNA methylation 1028 samples Submitted 2016/07/05 Platform GPL13534
At a glance

DNA methylation · human · 1028 samples

What it is
DNA methylationChemical marks on DNA that help switch genes on or off.
Organism
Homo sapiens (human)
Samples
1028 samples: 245 distinct titles, 41 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)
Systematic studies of the cancer genome are providing unprecedented insights into the molecular nature of human cancer. Using this information to guide the development and application of therapies in the clinic remains challenging. Here we report how cancer driving alterations detected in 11,215 tumors and 29 different tissues (integrating multiple omics) correlate with response to 265 compounds profiled in 1,001 cancer cell lines.
Read the full summary ↓
We find that cell lines faithfully resemble tumours on the domain of these alterations, and numerous examples of altered genes and pathways conferring drug sensitivity and resistance. Significantly, logic-based modeling improves our ability to identify drug sensitive sub-types and machine-learning methods enable us to investigate the predictive ability of the different data-omics. We provide a comprehensive analysis of how somatic alterations identified from the large-scale analysis of primary tumors impact on drug response. This represents a rich resource to help identify therapeutic options for selected cancer populations.
This dataset
Open GSE68379 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 (GSE68379_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 PRJNA282584. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 27397505) ↗
Study design
245 distinct titles, 41 of them repeated
CellLine_HCC ×24 CellLine_H ×19 CellLine_A ×13 CellLine_CAL ×11 CellLine_COLO ×11 CellLine_EW ×10 CellLine_COR-L ×9 CellLine_HT ×9 +33 more

How we read this: Read from the first 400 of 1028 sample titles: 245 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

+ 988 more — browse all 1028 samples with per-sample file links →

Datasets on a similar topic

Search all human methylation datasets in GEO →

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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.