Title |
CoINcIDE: A framework for discovery of patient subtypes across multiple datasets
|
---|---|
Published in |
Genome Medicine, March 2016
|
DOI | 10.1186/s13073-016-0281-4 |
Pubmed ID | |
Authors |
Catherine R. Planey, Olivier Gevaert |
Abstract |
Patient disease subtypes have the potential to transform personalized medicine. However, many patient subtypes derived from unsupervised clustering analyses on high-dimensional datasets are not replicable across multiple datasets, limiting their clinical utility. We present CoINcIDE, a novel methodological framework for the discovery of patient subtypes across multiple datasets that requires no between-dataset transformations. We also present a high-quality database collection, curatedBreastData, with over 2,500 breast cancer gene expression samples. We use CoINcIDE to discover novel breast and ovarian cancer subtypes with prognostic significance and novel hypothesized ovarian therapeutic targets across multiple datasets. CoINcIDE and curatedBreastData are available as R packages. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 2 | 17% |
Spain | 2 | 17% |
United Kingdom | 2 | 17% |
Unknown | 6 | 50% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 7 | 58% |
Scientists | 4 | 33% |
Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 2% |
United States | 1 | 2% |
Unknown | 63 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 18 | 28% |
Student > Ph. D. Student | 13 | 20% |
Student > Master | 7 | 11% |
Other | 4 | 6% |
Student > Postgraduate | 3 | 5% |
Other | 11 | 17% |
Unknown | 9 | 14% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 17 | 26% |
Biochemistry, Genetics and Molecular Biology | 10 | 15% |
Medicine and Dentistry | 10 | 15% |
Computer Science | 7 | 11% |
Engineering | 5 | 8% |
Other | 6 | 9% |
Unknown | 10 | 15% |