This package is useful in finding and validating predictive gene signature for classifying low risk versus high risk patients in early phase clinical trials. The primary end point is survival, and classification of cancer patients into low risk or high risk groups is mainly based on median cutoff, but others can be considered as well. It can also accommodate the prognostic factors if any. Both statistical and machine learning techniques are integrated as validating suit. The package can be used to perform the analysis using the entire samples and can also be used to carryout large scale cross validations. For the first instance, package reduces larger gene expression matrix to smaller version using supervised principle components analysis. Later entire validation procedure can be performed using reduced gene expression matrix with various types of validation schemes.
| Version: | 1.0 |
| Depends: | glmnet, graphics, gplots, pls, survival, DLBCL, superpc, utils, methods, stats, Biobase |
| Published: | 2013-01-15 |
| Author: | Pushpike Thalikarathne and Ziv Shkedy |
| Maintainer: | Pushpike Thalikarathne <Pushpike at gmail.com> |
| License: | GPL-3 (see file LICENCE) |
| NeedsCompilation: | no |
| In views: | Survival |
| CRAN checks: | aBioMarVsuit results |
| Package source: | aBioMarVsuit_1.0.tar.gz |
| MacOS X binary: | aBioMarVsuit_1.0.tgz |
| Windows binary: | aBioMarVsuit_1.0.zip |
| Reference manual: | aBioMarVsuit.pdf |
| Vignettes: |
R package for testing and validating biomarkers for predicting survival outcome. |
| News/ChangeLog: | NEWS |