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Availability

You can checkout the code from GitHub: git@github.com:ratschlab/MiTie.git

The the code is now written in C++ with shell script wrappers. We convert the transcript 
prediction task into a general mixed integer optimization problem and use third party solvers 
for this. We currently support CPLEX and glpk. Due to the significantly better runtime we 
recommend using CPLEX if you have many samples or many complex splice structures. This is 
a proprietary software, but free academic licenses can be obtained.

Setup

Installation:

change into the src directory and type

./configure -glpk-dir=<path_to_glpk>

or

./configure -cplex-dir=<path_to_cplex>

and then

make

mitie_example.sh demonstrates two strategies (with and without a genome annotation) to 
run MiTie on a tiny toy data set.

Parallelization:

MiTie stores splice graphs in an HDF5 file. You can run the transcript_prediction for 
each graph in that file in parallel.

Support:

We are happy to hear about your suggestions to improve the software. If you encounter 
any difficulties please let us know. We are also happy to implement additional features, 
if they are of general interest.


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The RNA-seq transcript predictor for multiple samples

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