URSA (Unknown RNA Sample Annotation) provides a tissue-specific but
genomic view for gene expression assays. It simulatenously computes
the estimated probabilities for hundreds of tissue/cell-types.
Cell-type models are constructed from more than ten thousand manually
curated samples from GEO, and then aggregated using Bayesian Correction
previously described in Barutcuoglu et al. 2006. Models and parameters
have been tuned for HG-U133 Plus 2.0 samples, but also have been shown
effective for other genome-scale expression assays after quantile
URSA was created by the Laboratory for bioinformatics and Functional
Genomics in the Lewis-Sigler Institue for Integrative Genomics at
See http://ursa.princeton.edu for more information.
URSA requires two external libraries:
The current implementation has been tested on Liblinear 1.8 and smile_1_1_linux64_gcc_4_4_5
Before typing 'make' to build 'ursa_predict' programs, users must
first download both external libraries and create soft links to
the associated directories.
ln -s <smile_directory> smile
ln -s <liblinear_directory> liblinear