What is NeoVar predictor?

NeoVar predictor is a tool to predict the functional significance of nonsynonymous variants of more than 50 proteins involved in neonatal diseases from the Clinical and Translational Bioinformatics research group at Vall d'Hebron Institute of Research.

How can I predict my variant?

You can submit your variant in our query page indicating the native amino acid, the residue and the mutated amino acid. Afterwards, you will be redirect to the prediction page.

Why is my variant not accepted?

We use as a reference the database UniProt, a comprehensive, high-quality and freely accessible resource of protein sequence and functional information. In particular, we use the most prevalent isoform, the canonical isoform. So, if you are using another isoform or another database for protein sequence reference such as NCBI or Ensembl, you can find some small diferences.

Which metrics has a prediction?

We provide you with three metrics:

  • Predictor: the best predictor for the protein among PON-P2, PolyPhen-2, SIFT and CADD

  • Label: the variants are classified as pathogenic or neutral according to its functional consequence.

  • Score: the numerical score of the functional consequence of the variant.

Score Plot

How are these predictions calculated?

These predictions are calculated by selecting the best predictor for each protein among PON-P2, PolyPhen-2, SIFT and CADD. To develop the predictor, we followed these steps:

  1. Collect the pathogenic and neutral variants of the proteins

  2. Gather the predictions of the variants for each predictor

  3. Estimate the performance for each predictor

  4. Select the best predictor per protein

Which is the performance of NeoVar predictor?

The NeoVar predictor have been evaluated and compared to the state of the art predictors. The Matthews Correlation Coefficient (MCC) per gene and predictor is:

In mean, the performance metrics per predictor are:

Sensitivity Specificity Accuracy MCC Coverage
NeoVar predictor 0.946 0.908 0.924 0.803 55 %
PON-P2 0.866 0.892 0.905 0.741 49 %
PolyPhen-2 0.846 0.899 0.857 0.652 99 %
CADD 0.961 0.67 0.788 0.571 27 %
SIFT 0.0 0.0 0.0 0.0 0 %

Can I download all the predictions for my protein?

You can download all the pre-calculated predictions to make your own queries. The file is in csv format containing the following columns:

# Field Description
1 Gene HGNC official gene symbol
2 Protein Uniprot accession number
3 Variant Nonsynonymous variant from the canonical isoform
4 Prediction Predicted functional consequence of the variant
5 Score Numerical score of the pathogenic prediction

Which other relevant information do you provide?

The results report a great amount of information related to the variant divided in different sections:

  • Prediction: prediction of the functional consequence of the variant along with its score and predictor.

  • Other Predictors: functional consequence of the variant predicted by other standard tools such as PON-P2, PolyPhen-2, SIFT and CADD predictors.

  • Variant Annotation: known the clinical evidence, biological relevance, population allele frequency and other information about your vairant from several databases such as ClinVar, UniProt, dbSNP and ExAC.

  • Biomedical Information: links to several resources about the disease (DECIPHER, HPO, GeneReview, Malacards, MedGen, OMIM and Orphanet databases), the protein (UniProt database), the tridimensional structure (PDB database), the protein-protein interactions (STRING database), the metabolic pathways (REACTOME database), and the gene (Ensembl, GeneCards, HGNC and NCBI databases).

  • Protein Plot: distribution of several features along the protein such as known pathogenic and neutral variants, biological relevant residues, functional domains and gene exons.

  • Predicted functional consequence: localization of the score of the variant in the distribution of scores of known pathogenic and neutral variants.

  • Explanatory variables of the prediction: localization of the features of the variant in the distribution of features of known pathogenic and neutral variants.