In this study, we present a flexible framework to assess different combinations of computational algorithms and kinase-substrate libraries for the inference of kinase activities. For the benchmark, we use a set of kinase perturbation experiments to evaluate which combination is able to recapitulate the perturbed kinases from the phosphoproteomics data. Additionally, we propose a new benchmarking strategy based on multi-omics tumor data.
If you want to test your own method try out our package benchmarKIN and check out the documentation.
If you would like to access any of the files used in our publication, please check out our Zenodo repository.
We have included the following kinase-substrate libraries:
- PhosphoSitePlus
- PTMsigDB
- Omnipath
- Gold Standard set of GPS 6.0
- iKiP-db
- NetworKIN
Additionally have tested the combination with predicted targets including the Kinase Library and Phosformer.
We have included the following methods for the comparison:
- fgsea
- Fisher's exact test
- KARP
- KSEA
- Kologomorov-Smirnov
- linear model - RoKAI
- Mann-Whitney-U test
- mean
- median
- multivatiate linear model - decoupler
- normalised mean
- Principal Component Analysis
- PTM-SEA
- sum
- univariate linear model - decoupler
- upper quantile
- VIPER
- z-score
- X-square test
Mueller-Dott, Sophia, Eric J. Jaehnig, Khoi Pham Munchic, Wen Jiang, Tomer M. Yaron-Barir, Sara R. Savage, Martin Garrido-Rodriguez, et al. 2024. “Comprehensive Evaluation of Phosphoproteomic-Based Kinase Activity Inference.” bioRxiv. https://doi.org/10.1101/2024.06.27.601117.