README.Rmd

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HVSlimPred

This R package complements the performance evaluation analysis for the manuscript entitled "Identifying novel functional linear motifs using the host-viral protein interaction network and the principle of convergent evolution".

Installation

You can install the released version of HVSlimPred from gitlab with:

devtools::install_gitlab("https://gitlab.ebi.ac.uk/petsalakilab/hvslimpred")

Get Protein-level evaluation metrics

For protein-level enrichment, we measured the enrichment of true-positives in our predicted dataset using a one-tailed fisher-exact test, where the odds ratio represents the magnitude of the enrichment. True-positives are the number of motif-carrying proteins present in both the predicted dataset and the ELM dataset regardless of whether the predicted protein has the right motif or found in the right location

The output of the following command is a data frame containing all the relevant protein-level performance metrics for each domain enrichment filter in addition to the non-filtered qslim output.

library(HVSlimPred)
prot_eval_metrics = HV_prot_level_eval()

Get Motif-level evaluation metrics

For motif-level enrichment, we simply cannot use a binary classification as we did for protein-level evaluation because in reality, predicted motifs are partially correct to some extent as they might contain true-positive residues in a given sequence stretch, and therefore we used a re-implemented version of the evaluation protocol proposed in Prytuliak et al. 2017 instead of binary classification, where we computed the common performance metrics (Recall, precision F1, etc .. ) both residue-wise and site-wise given that the motif-carrying proteins are also found in the ELM benchmarking dataset. So this analysis was not performed on proteins not reported in the ELM dataset.

The output of the following command is a data frame containing all the relevant motif-level performance metrics for each domain enrichment filter in addition to the non-filtered qslim output.

library(HVSlimPred)
motif_eval_metrics = HV_motif_level_eval()

Get Protein-domain interactions evaluation metrics

For evaluating protein-domain interactions we measured the enrichment of true-positive interactions between a given motif-carrying protein and its associated domains as reported in the ELM interaction dataset. As in the motif-level evaluation, this analysis was performed only on the motif-carrying proteins reported in the ELM interactions dataset, where true-positives represents the number of correctly associated domains for a given motif-carrying protein and then summed over all motif-carrying proteins in the predicted dataset.

The output of the following command is a data frame containing all the relevant protein-domain interactions' performance metrics for each domain enrichment filter.

library(HVSlimPred)
ProtDom_int_eval_metrics = HV_prot_dom_int_eval()