Probabilistic Machine Learning
Dependency analysis of survival associated regions
daSAr: Dependency analysis of survival associated regions
The daSAr package extracts survival associated biomakers from multi-source functional genomics data as described in the paper Biomaker discovery via dependency analysis of multi-view functional genomics data. The method has been developed by the Statistical Machine Learning and Bioinformatics group at the Department of Information and Computer Science, Aalto University. When you use this method, please cite either of the following paper:
| Riku Louhimo, Viljami Aittomaki, Ali Faisal,Marko Laakso, Ping Chen, Kristian Ovaska, Erkka Valo, Leo Lahti, Vladimir Rogojin, Samuel Kaski, Sampsa Hautaniemi Systematic use of computational methods allows stratification of treatment responders in glioblastoma multiforme.. Systems Biomedicine 2013;1:130-136. |
| Ali Faisal, Riku Louhimo, Leo Lahti, Sampsa Hautaniemi and Samuel Kaski. Biomarker discovery via dependency analysis of multi-view functional genomics data. In Proceedings of NIPS 2011 Workshop: From Statistical Genetics to Predictive Models in Personalized Medicine. |
Installing and running
The software package runs under R, a free language and environment for statistical computing. The package is tested with the R version 2.12.0 in the Linux environment.
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Documentation and support
For documentation and examples, see the README file included in the package.
This is experimental software provided as is; we welcome any comments and corrections but cannot give any guarantees about the code. If you have any comments or bug reports, please direct them to Ali Faisal.