What is dbNSFP? 

dbNSFP is the leading database developed for functional prediction and annotation of all potential non-synonymous single-nucleotide variants (nsSNVs) in the human genome. Since its initial release in 2011, dbNSFP has established itself as the trusted data infrastructure powering regulatory-compliant clinical genomics platforms and advancing genetic research across academic and industry applications worldwide (Publications).

Its current version is based on the GENCODE release 48 (Ensembl version 114) and includes a total of 81,529,581 nsSNVs and 2,230,506 ssSNVs (splicing-site SNVs) of all known protein-coding genes in the human genome. 

dbNSFP includes:

Variant function prediction scores from 34 algorithms: 

• SIFT, SIFT4G, PROVEAN, Polyphen2-HDIV, Polyphen2-HVAR, MutationTaster 2021, MutationAssessor, FATHMM-XF coding, CADD, VEST4, DANN, MetaSVM, MetaLR, MetaRNN, Eigen, Eigen-PC, M-CAP, REVEL, MutPred2, MVP, gMVP, MPC, PrimateAI, DEOGEN2, ALoFT, BayesDel, ClinPred, LIST-S2, VARITY, ESM1b, AlphaMissense, PHACTboost, MutFormer, and MutScore.

Evolutionary conservation scores, including:

• PhyloP (3 versions), phastCons (3 versions), GERP++, GERP_91_mammals, and bStatistic.

ClinVar and observed allele frequency in large population genomic data sets to enhance rare VUS variant interpretation, including

• The 1000 Genomes Project, gnomAD v4.1 and v2.1.1 (including non-neuro, non-cancer, and control sample subsets), TOPMed, All of Us, RGC Million Exome, and ALFA (aggregated from dbGaP and dbSNP)

And gene functions and experiment data:

• Various gene IDs from HGNC for cross-referencing and integration

• Genetic disorders and phenotypes: GenCC, OMIM, Orphanet, The Human Phenotype Ontology, GWAS Catalog, ClinGen Dosage Sensitivity, etc.

• Protein function and structure: The Human Protein Atlas, UniProt, Gene Ontology, IntAct, etc.

• Metabolic and signaling pathways: consensusPathDB, KEGG pathway, etc.

• Model organism experiment data: MGI, ZFIN, etc.

For a full list of data and version information, please refer to the current README of dbNSFP in the Releases page.

Developer Collaboration

We welcome developers of functional prediction methods to provide their predictions and scores to the database. Please contact us at collaboration@dbnsfp.org.