The aim of PATHiPRED web tool is to take advantage of sub-pathway activation information to distinguish between two classes or a continuous variable. PATHiPRED uses the probability of activation of stimulus-response sub-pathways obtained with PATHiWAYS methodology to compute a pathway-based biomarkers predictor. PATHiPRED performs a SVM modelling with cross-validation. This methodology obtained the best results in a 5 cancer-related datasets study (Amadoz et al. in preparation). Moreover, previously obtained models could be used to predict new datasets from PATHiPRED results page.

PATHiWAYS and PATHiPRED tools are linked from results pages allowing users to perform both analyses with the same dataset.

1. Microarray normalization using the affy R library (Gautier et al., 2004) of Bioconductor (Gentleman et al., 2004) implemented in Babelomics platform (Medina et al., 2010).
2. Estimation of the probability of subpathways activation using the method proposed in Sebastián-León et al. (Sebastián-León et al., 2013).
3. Withdrawal of no variable subpathways between classes.
4. Subpathways probabilities correction by the number of nodes.
5. SVM modelling with selected subpathways using e1071 R library (Karatzoglou et al. 2006).

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