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 
Princeton University.

See http://ursa.princeton.edu for more information.


URSA requires two external libraries:
SMILE:	http://genie.sis.pitt.edu/about.html
LIBLINEAR: http://www.csie.ntu.edu.tw/~cjlin/liblinear/

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
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