Download¶
20/20+ releases¶
- 2020plus v1.2.3 - 4/6/2019 - Minor change for installation procedure
- 2020plus v1.2.2 - 9/10/2018 - Added option to handle mutational data sets where silent mutations are not reported
- 2020plus v1.2.1 - 8/2/2018 - Fixed bug where configuration file would not load
- 2020plus v1.2.0 - 3/21/2018 - Change to null distribution simulation
- 2020plus v1.1.3 - 8/17/2017 - Bug fixes for different versions of rpy2
- 2020plus v1.1.2 - 7/3/2017 - Further bug fixes for latest versions of 20/20+ dependencies
- 2020plus v1.1.1 - 5/22/2017 - Bug fixes to work with newest versions of pandas
- 2020plus v1.1.0 - 11/21/2016 - Improved training procedure and added p-value diagnostic plots
- 2020plus v1.0.3 - 10/12/2016 - Fixed error in logging
- 2020plus v1.0.2 - 10/03/2016 - Fixed python3 conversion bug
- 2020plus v1.0.1 - 6/26/2016 - Added ability to run 20/20+ as a pipeline
- 2020plus v1.0.0 - 5/1/2016 - Initial release
Necessary data files¶
- Pre-computed scores data set
- Reference SNVBox transcripts in BED format
Pre-trained classifier¶
We have trained a 20/20+ classifier on pan-cancer data. This can be used to predict on cancer type specific mutations.
Current trained classifier (>= v1.1.0):
- 2020plus_10k.Rdata (NUMSIMULATIONS=10,000, default)
- 2020plus_100k.Rdata (NUMSIMULATIONS=100,000)
Trained classifier for versions 1.0.0-1.0.3 (old):
Pan-cancer mutation data¶
- full pan-cancer data set from:
Collin J. Tokheim, Nickolas Papadopoulos, Kenneth W. Kinzler, Bert Vogelstein, and Rachel Karchin. Evaluating the evaluation of cancer driver genes. PNAS 2016 ; published ahead of print November 22, 2016, doi:10.1073/pnas.1616440113
Details about how the mutations were filtered is available here.
Example data¶
- Example pan-cancer data set