A mathematical descriptor of tumor mesoscopic-structure from computed tomography images annotates prognostic and molecular phenotypes of epithelial ovarian cancer

Published: 15 December 2018| Version 2 | DOI: 10.17632/4c5znk5m8t.2
Contributors:
Haonan Lu,
Mubarik Arshad,
Andrew Thornton,
Giacomo Avesani,
Paula Cunnea,
Ed Curry,
Fahdi Kanavati,
Jack Liang,
Katherine Nixon,
Sophie Williams,
Mona Hassan,
David Bowtell,
Hani Gabra,
Christina Fotopoulou,
Andrea Rockall,
Eric Aboagye

Description

The clinical, radiomics and proteomics data to reproduce the key findings in 'A mathematical descriptor of tumor mesoscopic-structure from computed tomography images annotates prognostic and molecular phenotypes of epithelial ovarian cancer'. Radiomics data for both the HH and the TCGA cohort are scaled and centered; RPV and eRPV (Affymentrix U133) are included in the clinical dataframes; Normalised, log2 transformed and median centered proteomics data are provided from reverse phase protein array (RPPA).

Files

Steps to reproduce

See ROCS_Rscript.

Institutions

Imperial College London

Categories

Proteomics, Biomedical Imaging

License