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Indices of Tolerance (IOT): Cross-platform biomarkers that identify kidney transplant tolerance

GSE14655 Homo sapiens (human) Expression microarray 237 samples Submitted 2010/05/25 Platform GPL8136
At a glance

Expression microarray · human · 237 samples

What it is
Expression microarrayGene activity read on a chip (the older technology that RNA-seq replaced).
Organism
Homo sapiens (human)
Samples
237 samples
Data you can get
A processed expression table (series matrix) and the array files, from NCBI.
Summary (written by the submitters)
Being able to identify patients in whom immunological tolerance has been established or is developing would allow an individually tailored approach to post-transplant management of kidney allograft recipients.
Read the full summary ↓
Ex vivo immunological monitoring was performed on samples from five groups of European renal transplant recipients (“IOT samples”): ten drug-free tolerant recipients who were functionally stable despite remaining immunosuppression-free for more than one year (Tol-DF); also functionally stable patients on minimal immunosuppression (<10 mg/day prednisone, s-LP); stable patients maintained with calcineurin inhibitors (s-CNI); stable patients maintained on CNI-free immunosuppression regimen (s-nCNI); patients showing signs of chronic rejection (CR) and healthy controls (HC). Among the investigation of other biomarkers and bioassays, gene expression profiles were generated on custom Agilent 8x15K 60mer oligonucleotide microarrays (“RISET 2.0”) on the IOT cohort (training set) and on an independent cohort of patients from the ITN (USA) that contained similar groups of patients and included 23 tolerant recipients (“ITN samples”, test set). Set of genes were identified, whose expression on whole blood allowed the identification of 100% of the tolerant recipients in the training set and 84% in the test set. Keywords: classification of clinical samples, tolerance prediction
This dataset
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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 (GSE14655_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 PRJNA112341. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 20501943) ↗
Samples in this study

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