FORECAST

Published: 11 November 2024| Version 4 | DOI: 10.17632/cd9cf2fb76.4
Contributors:
George Cresswell, Javier Fernandez Mateos, Andrea Sottoriva, Nicholas Trahearn, chela james

Description

Measuring tumour evolvability metrics to predict recurrence in advanced localised prostate cancer using multi-biopsy targeted sequencing of prostate cancer specific genes, low coverage whole genome sequencing and matching image analysis. Version 4 note: cell_classes.zip corrected to easier formatting, sequenced_subregions.zip added to identify regions sequenced within slide images and Forecast ID reference added to allow for conversion from slide IDs to sequencing IDs.

Files

Steps to reproduce

Code for analysis can be found on the GitHub for our lab (https://github.com/sottorivalab).

Institutions

Institute of Cancer Research Sutton

Categories

Genomics, Prostate Cancer, Mutation

Licence