Oomycete Effector Prediction
We have developed a pipeline, EffectorO, that uses two complementary approaches to predict effectors in oomycete pathogen genomes: (1) a machine learning-based pipeline that incorporates amino acid sequence properties as features and is trained on both experimentally-verified oomycete effectors and (2) a pipeline based on lineage-specificity to find proteins that are unique to one species or genus, a sign of evolutionary divergence due to adaptation to the host.
Resources:
- All code is on Github here: https://github.com/mjnur/oomycete-effector-prediction
- The EffectorO-ML classifier can be run as a webapp here: https://effectoro.onrender.com/
- The publication can be found at: https://www.biorxiv.org/content/10.1101/2021.03.19.436227v2
