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 prediction for total Human Proteome is available here. |
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PON-P2 API PON-P2 can be accessed programmatically by using an application programming interface (API) or through Variant Effect Predictor (VEP) by using a plugin PON_P2. PON-P2 API allows users to submit variants in a Variant Call Format (VCF) file. Currently, PON-P2 predicts pathogenicity of variations in human genome reference version hg19. We have added a new feature to the API. The users can submit variations in the human genome reference hg38 which will be subsequently mapped to hg19 using liftover tool before making predictions. Note: We are still testing our API service and VEP Plugin. Therefore, we kindly request our users to try them and let us know in case of any problem. | ||||||||
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Requirements for VEP Plugin: 1. VEP and PON_P2 plugin
First you need to install VEP from http://www.ensembl.org/info/docs/tools/vep/index.html. You can also download the PON_P2 plugin using the following link. 2.Python To use PON_P2 Plugin for VEP, you need python installed in your computer. Python is pre-installed on most Linux distributions and MAC OS X. On Windows, you can download python from python.org. 3. SUDS client for SOAP We use Simple Object Access Protocol (SOAP) to connect to PON-P2 server. You need to install Suds web services client from here. 4. PON-P2 script
We have prepared a python script to support VEP Plugin to connect to PON-P2 server. You can download the script from here. | ||||||||
PON-P2 results PON-P2 classifies amino acid substitutions into three classes: Pathogenic, Neutral and Unknown. PON-P2 is an ensembl classifier using 200 independent classifiers. If at least 95% of the classifiers (190 out of 200) predict a variant to be pathogenic or neutral, the variant is classified as Pathogenic or Neutral. If 95% of the predictor do not agree on one class, the variant is predicted as Unknown. Along with the classification, a probability of pathogenicity is predicted for each variation. |