This repository is the working directory for the Garnet-Forest bundle of python scripts for analyzing diverse forms of 'omic' data in a network context.
These changes relate to running Forest with msgsteiner-1.1 instead of msgsteiner-1.3. The new version fixes the bug described in #17 and can identify lower cost optimal forests. For our A549 example, it returns the same nodes but replaces two edges. This yields a lower overall edge cost.
Specific changes include:
Update the README to recommend msgsteiner-1.3 and link to the new version (still link to the old site for the licence terms)
Update Travis CI testing to use msgsteiner-1.3
Write the objective function score to the info file to verify msgsteiner-1.3 improves the forest
Update some of the unit tests to test that the objective function is computed correctly
Update the reference files for the A549 integration test to match the msgsteiner-1.3 output
@AmandaKedaigle Can you please update http://fraenkel-nsf.csbi.mit.edu/omicsintegrator/ to match the changes I made in the README? Specifically, recommending msgsteiner-1.1 and linking to the new code on Alfredo's site.
@aabaker99 I updated some of your unit tests to check the objective function value. This was primarily to verify my calculation of the objective function in forest.py. I don't think we need to verify this in every unit test.
I'll merge this at the end of the week if there are no comments.
These changes relate to running Forest with msgsteiner-1.1 instead of msgsteiner-1.3. The new version fixes the bug described in #17 and can identify lower cost optimal forests. For our A549 example, it returns the same nodes but replaces two edges. This yields a lower overall edge cost.
Specific changes include:
@AmandaKedaigle Can you please update http://fraenkel-nsf.csbi.mit.edu/omicsintegrator/ to match the changes I made in the README? Specifically, recommending msgsteiner-1.1 and linking to the new code on Alfredo's site.
@aabaker99 I updated some of your unit tests to check the objective function value. This was primarily to verify my calculation of the objective function in forest.py. I don't think we need to verify this in every unit test.
I'll merge this at the end of the week if there are no comments.