dbSNP: the NCBI database of genetic variation

By S. Sherry, Minghong Ward, M. Kholodov, J. Baker, Lon Phan, Elizabeth M. Smigielski, K. Sirotkin. 2001

7,312 citations recorded by the source corpus.

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In Genetics

In Molecular Biology

Citations in the corpus

SIFT web server: predicting effects of amino acid substitutions on proteins (2012, background): “Databases like dbSNP (4) and 1000 Genomes (5) are useful for filtering out common variants, but the remaining variants need to be sorted and prioritized to identify those that may potentially affect protein function.”
ProViz—a web-based visualization tool to investigate the functional and evolutionary features of protein sequences (2016, background): “Furthermore, single nucleotide polymorphisms (SNPs) can disrupt the normal function of these modules often resulting in deleterious outcomes that underlie disease (14,15).”
Genomic variant annotation and prioritization with ANNOVAR and wANNOVAR (2015, background): “…Project 31 and the US National Institutes of Health–National Heart, Lung, and Blood Institute (NIH-NHLBI) ESP6500 exome-sequencing project 32 ; finding the SIFT 33 and PolyPhen 34 scores for nonsynonymous variants; and identifying the presence or absence of a variant in the dbSNP database 35 .”
Recon3D: A Resource Enabling A Three-Dimensional View of Gene Variation in Human Metabolism (2018, positive): “We analyzed SNP data from multiple gene variation databases (dbSNP 30 , UniProt 24 , PharmGKB 31 ) and assessed whether the 3D location of variants in a gene could, in general, discern whether mutations were deleterious or tolerated 41 .”
New approach for understanding genome variations in KEGG (2018, methodology): “The KEGG VARIANT database also contains links to outside databases such as ClinVar (5), dbSNP (6) and COSMIC (7).”
Variation Interpretation Predictors: Principles, Types, Performance, and Choice (2016, methodology): “The dbSNP database [Sherry et al., 2001] is a very large database for short variants and contains data from The 1000 Genomes Project (http://www.1000genomes.org/).”
The human splicing code reveals new insights into the genetic determinants of disease (2014, methodology): “Themodel was further evaluated using genome-wide SNVs, including common SNPs in dbSNP135 (17), point mutations in HGMD (18), and rare variants from ANNOVAR (55).”
Disease-related mutations predicted to impact protein function (2012, methodology): “This comprehensive new resource integrates variants from dbSNP [14], Swiss-Prot [15], PMD [16], and OMIM [17] and annotations of functional effects (from Swiss-Prot and PMD) and disease (from SwissVar [18], PMD and OMIM).”
Performance of computational tools in evaluating the functional impact of laboratory-induced amino acid mutations (2012, background): “A frequency distribution showing the number of different mutants explored in the laboratory for 2372 human proteins, as reported in the UniProt database.”
Genome graphs and the evolution of genome inference (2017, background): “These observed flanking sequences (perhaps obtained by Sanger sequencing), rather than a VCF position, defined the variant (Sherry et al. 2001).”
The UCSC Genome Browser database: 2017 update (2016, background): “Major variant annotation tracks include small variations from NCBI’s dbSNP database (35), including tracks for older dbSNP releases in human assemblies, along with variant calls and high-confidence regions from the 1000 Genomes Consortium (36).”
Pseudomonas Genome Database: improved comparative analysis and population genomics capability for Pseudomonas genomes (2010, methodology): “Polymorphisms in genomic DNA, cDNA and amino acid sequences were also assigned a standardized description following recommendations made by the Human Genome Variation Society (13), a standard adopted by other SNP databases including dbSNP (14) and Ensembl (15).”
Long‐term expanding human airway organoids for disease modeling (2019, neutral): “The obtained variants were annotated using four germline databases: PONvs2 (1.762 individuals — WGS; https://github.com/hartwigmedical), GoNL V5 (750 individuals — WGS; Boomsma et al , 2014), GNOMAD (15.496 individuals — WGS; Lek et al , 2016), and dbSNP 137.b37 (Sherry et al , 2001).”