genes drive tumor development. Identifying cancer driver genes is critical
for precision oncology. Most of current approaches either identify driver
genes based on mutational recurrence or using estimated scores predicting
the functional consequences of mutations. 'driveR' is a tool for
in Ulgen E, Sezerman OU. 2020. driveR: A Novel Method for Prioritizing Cancer

Imports: caret, randomForest, GenomicRanges, GenomeInfoDb,

in Ulgen E, Sezerman OU. 2021. driveR: driveR: a novel method for
prioritizing cancer driver genes using somatic genomics data. BMC

Title: Regression and association models for clustered categorical responses
Description: Fit regression and association models for clustered categorical
responses using dependence ratio as a measure of association
Packaged: Mon Feb 12 13:53:50 2007; jjoj

Title: Regression and association models for repeated categorical data
Description: Likelihood-based marginal regression and association modelling for repeated, or otherwise clustered, categorical responses using dependence ratio as a measure of the association
Packaged: Wed Feb 14 01:52:29 2007; jukkaj

Packaged: Fri Mar  2 13:06:33 2007; jukkaj

Packaged: Fri Dec 28 16:23:25 2007; jukkaj

Packaged: Wed Feb 13 23:32:35 2008; jukkaj

Description: Likelihood-based marginal regression and association
modelling for repeated, or otherwise clustered, categorical
responses using dependence ratio as a measure of the

Title: Dual empirical likelihood inference under density ratio models
Description: Dual empirical likelihood (DEL) inference under semiparametric density ratio models (DRM) for multiple samples, including quantile estimatoin, density estimation, composite hypothesis testing of the equality of distributoin functions, etc.

Description: Dual empirical likelihood (DEL) inference under semiparametric density ratio models (DRM) for multiple samples, including quantile estimation and comparison, density estimation, composite hypothesis testing for changes in distribution functions, etc.

Title: Dual Empirical Likelihood Inference under Density Ratio Models
Description: Dual empirical likelihood (DEL) inference under semiparametric density ratio models (DRM) in the presence of multiple samples, including population cumulative distribution function estimation, quantile estimation and comparison, density estimation, composite hypothesis testing for DRM parameters which encompasses testing for changes in population distribution functions as a special case, etc.