González-Pérez, AbelLópez Bigas, Núria2017-01-262017-01-262015-10http://hdl.handle.net/10230/27994OncodriveFM depends on Python 3 and some external libraries, numpy, scipy, pandas and statsmodels./nThe easiest way to install all this software stack is using the well known Anaconda Python distribution./nThen to get OncodriveFM installed run the following command:/n(env) $ pip install oncodrivefm/nAnd that's all. The following command will allow you to check that is correctly installed by showing the command help:/n(env) $ oncodrivefm --help/nusage: oncodrivefm [-h] [-o PATH] [-n NAME] [--output-format FORMAT]/n [-N NUMBER] [-e ESTIMATOR] [--gt THRESHOLD]/n [--pt THRESHOLD] [-s SLICES] [-m PATH] [--save-data]/n [--save-analysis] [-j CORES] [-D KEY=VALUE] [-L LEVEL]/n DATA/nCompute the FM bias for genes and pathways/npositional arguments:/n DATA File containing the data matrix in TDM format/noptional arguments:/n -h, --help show this help message and exit/n -o PATH, --output-path PATH/n Directory where output files will be written/n -n NAME Analysis name/n --output-format FORMAT/n The FORMAT for the output file/n -N NUMBER, --samplings NUMBER/n Number of samplings to compute the FM bias pvalue/n -e ESTIMATOR, --estimator ESTIMATOR/n Test estimator for computation./n --gt THRESHOLD, --gene-threshold THRESHOLD/n Minimum number of mutations per gene to compute the FM/n bias/n --pt THRESHOLD, --pathway-threshold THRESHOLD/n Minimum number of mutations per pathway to compute the/n FM bias/n -s SLICES, --slices SLICES/n Slices to process separated by commas/n -m PATH, --mapping PATH/n File with mappings between genes and pathways to be/n analysed/n --save-data The input data matrix will be saved/n --save-analysis The analysis results will be saved/n -j CORES, --cores CORES/n Number of cores to use for calculations. Default is 0/n that means all the available cores/n -D KEY=VALUE Define external parameters to be saved in the results/n -L LEVEL, --log-level LEVEL/n Define log level: debug, info, warn, error, critical,/n notsetOncodriveFM detects candidate cancer driver genes and pathways from catalogs of somatic mutations in a cohort of tumors by computing the bias towards the accumulation of functional mutations (FM bias).This novel approach avoids some known limitations of recurrence-based approaches, such as the difficulty to estimate background mutation rate, and the fact that they usually fail to identify lowly recurrently mutated driver genes.engUniversitat Pompeu Fabra Free Source Code License Agreement. Consulteu les condicions d'ús específiques dins del document.info:eu-repo/semantics/otherhttps://doi.org/10.34810/data413CancerGenesDriverFunctional mutationsinfo:eu-repo/semantics/openAccess