@@ -39,9 +39,7 @@ The installation procedure works correctly with recent versions of Linux (Ubuntu
## Running WARIO
To run WARIO to characterize an ensemble, the user can directly execute the [contact_clustering](https://gitlab.laas.fr/moma/methods/analysis/WARIO/-/blob/main/wario/contact_clustering.ipynb) notebook, which contains the detailed pipeline and allows a step-by-step implementation of the tool.
The notebook takes a conformational ensemble as input and returns the weighted family of contact maps that characterizes the ensemble. The data featurization is performed at a first stage, allowing the user to adjust the resolution of the clustering algorithm afterwards. Then, clustering and post-processing are performed, and the results are displayed and saved.
To run WARIO to characterize an ensemble, the user can directly execute the [contact_clustering](https://gitlab.laas.fr/moma/methods/analysis/WARIO/-/blob/main/wario/contact_clustering.ipynb) notebook, which contains the detailed pipeline and allows a step-by-step implementation of the tool. The notebook takes a conformational ensemble as input and returns the weighted family of contact maps that characterizes the ensemble. The data featurization is performed at a first stage, allowing the user to adjust the resolution of the clustering algorithm afterwards. Then, clustering and post-processing are performed, and the results are displayed and saved.
### Input data
...
...
@@ -90,3 +88,14 @@ Structural properties such as the average DSSP propensities of each cluster can
## Large ensembles
The current implementation of WARIO can be run in a normal desktop computer for ensembles with $nL\lessapprox 3\cdot 10^7$. Limitations are mainly due to memory constraints. We are currently working on a more efficient implementation for large ensembles, which can be run in remote servers. Until it will be released, we can [provide guidance](mailto:javier.gonzalezdelgado@mcgill.ca) on how to run the current code in limiting settings $nL\approx 3-4\cdot 10^7$ more efficiently.
