PON-P2

PON-P2 predicts the pathogenicity (harmfulness) of amino acid substitutions. It is a machine learning-based approach and utilizes amino acid features, Gene Ontology (GO) annotations, evolutionary conservation, and if available, annotations of functional sites. Note that, PON-P2 is NOT a meta-predictor. PON-P2 estimates the reliability of predictions and groups the variants into pathogenic, neutral and unknown classes. Read more

Performance of PON-P2 has been extensively tested. For details, see here. Performance of PON-P2 on additional datasets such as predictSNPSelected and SwissVarSelected datasets are also available here. PON-P2 has been shown to work also on cancer variants. PON-P2 predictions for amino acid substitutions in COSMIC (v68) and data published in Harmful somatic amino acid substitutions affect key pathways in cancers is publicly available here.

PON-P2 was the best performing method in a recent comparison and outperformed protein-specific predictors in 85% of the proteins (Riera et. al. 2016).

NEWS: PON-P2 API and a VEP Plugin for PON-P2 is now available.

'
Home News Instructions Disclaimer Useful Links Cancer variant predictions

PON-P2 Prediction

Identifier submission Genomic submission Sequence submission PON-P2
API
VEP
Plugin

Genomic co-ordinate(s) and variation(s)
Example:
3:49044874,+1,C,T
11:108368994,-1,G,C
16:11363014,-1,A,G

Or upload genomic variation(s) as file (max. 20MB):


Or submit your variations in VCF format file (max. 20MB)


Email (Please provide your e-mail address to get the results when they are ready. There have been problems to attach results to email ids ending ...@hotmail... So, please use other email id if possible.)