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Open AccessJournal ArticleDOI

dbNSFP v2.0: A Database of Human Non-synonymous SNVs and Their Functional Predictions and Annotations

TLDR
Rich functional annotations for SNVs and genes have been added into the new version, including allele frequencies observed in the 1000 Genomes Project phase 1 data and the NHLBI Exome Sequencing Project, various gene IDs from different databases, functional descriptions of genes, gene expression and gene interaction information, among others.
Abstract
dbNSFP is a database developed for functional prediction and annotation of all potential non-synonymous single-nucleotide variants (nsSNVs) in the human genome. This database significantly facilitates the process of querying predictions and annotations from different databases/web-servers for large amounts of nsSNVs discovered in exome-sequencing studies. Here we report a recent major update of the database to version 2.0. We have rebuilt the SNV collection based on GENCODE 9 and currently the database includes 87,347,043 nsSNVs and 2,270,742 essential splice site SNVs (an 18% increase compared to dbNSFP v1.0). For each nsSNV dbNSFP v2.0 has added two prediction scores (MutationAssessor and FATHMM) and two conservation scores (GERP++ and SiPhy). The original five prediction and conservation scores in v1.0 (SIFT, Polyphen2, LRT, MutationTaster and PhyloP) have been updated. Rich functional annotations for SNVs and genes have also been added into the new version, including allele frequencies observed in the 1000 Genomes Project phase 1 data and the NHLBI Exome Sequencing Project, various gene IDs from different databases, functional descriptions of genes, gene expression and gene interaction information, among others. dbNSFP v2.0 is freely available for download at http://sites.google.com/site/jpopgen/dbNSFP.

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Citations
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Journal ArticleDOI

The Ensembl Variant Effect Predictor.

TL;DR: The Ensembl Variant Effect Predictor can simplify and accelerate variant interpretation in a wide range of study designs.
Journal ArticleDOI

REVEL: An Ensemble Method for Predicting the Pathogenicity of Rare Missense Variants

Nilah M. Ioannidis, +45 more
TL;DR: This work developed REVEL (rare exome variant ensemble learner), an ensemble method for predicting the pathogenicity of missense variants on the basis of individual tools: MutPred, FATHMM, VEST, PolyPhen, SIFT, PROVEAN, MutationAssessor, LRT, GERP, SiPhy, phyloP, and phastCons.
Journal ArticleDOI

The Human Gene Mutation Database: towards a comprehensive repository of inherited mutation data for medical research, genetic diagnosis and next-generation sequencing studies

TL;DR: The Human Gene Mutation Database constitutes de facto the central unified gene/disease-oriented repository of heritable mutations causing human genetic disease used worldwide by researchers, clinicians, diagnostic laboratories and genetic counsellors, and is an essential tool for the annotation of next-generation sequencing data.
Journal Article

A High-Resolution Map of Human Evolutionary Constraint Using 29 Mammals

TL;DR: The comparison of related genomes has emerged as a powerful lens for genome interpretation as mentioned in this paper, which reveals a small number of new coding exons, candidate stop codon readthrough events and over 10,000 regions of overlapping synonymous constraint within protein-coding exons.
References
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Journal ArticleDOI

A method and server for predicting damaging missense mutations.

TL;DR: A new method and the corresponding software tool, PolyPhen-2, which is different from the early tool polyPhen1 in the set of predictive features, alignment pipeline, and the method of classification is presented and performance, as presented by its receiver operating characteristic curves, was consistently superior.
Journal ArticleDOI

ANNOVAR: functional annotation of genetic variants from high-throughput sequencing data

TL;DR: The ANNOVAR tool to annotate single nucleotide variants and insertions/deletions, such as examining their functional consequence on genes, inferring cytogenetic bands, reporting functional importance scores, finding variants in conserved regions, or identifying variants reported in the 1000 Genomes Project and dbSNP is developed.
Journal ArticleDOI

An integrated map of genetic variation from 1,092 human genomes

TL;DR: It is shown that evolutionary conservation and coding consequence are key determinants of the strength of purifying selection, that rare-variant load varies substantially across biological pathways, and that each individual contains hundreds of rare non-coding variants at conserved sites, such as motif-disrupting changes in transcription-factor-binding sites.
Journal ArticleDOI

Predicting the effects of coding non-synonymous variants on protein function using the SIFT algorithm.

TL;DR: This protocol describes the use of the 'Sorting Tolerant From Intolerant' (SIFT) algorithm in predicting whether an AAS affects protein function.
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