Cited by 38Genomics and Rare DiseasesGenetic Associations and EpidemiologyGenomics and Phylogenetic Studies

VIPdb, a genetic variant impact predictor database

Open access
Hu, Zhiqiang, Yu, Changhua, Furutsuki, Mabel, Andreoletti, Gaia, Ly, Melissa, Hoskins, Roger, Adhikari, Aashish N., Brenner, Steven E.·2019·Human Mutation

Abstract

Genome sequencing identifies vast number of genetic variants. Predicting these variants' molecular and clinical effects is one of the preeminent challenges in human genetics. Accurate prediction of the impact of genetic variants improves our understanding of how genetic information is conveyed to molecular and cellular functions, and is an essential step towards precision medicine. Over one hundred tools/resources have been developed specifically for this purpose. We summarize these tools as well as their characteristics, in the genetic Variant Impact Predictor Database (VIPdb). This database will help researchers and clinicians explore appropriate tools, and inform the development of improved methods. VIPdb can be browsed and downloaded at https://genomeinterpretation.org/vipdb.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/humu.23858

Cites

179 of 180 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • SIFT, PolyPhen-2, and CADD were among the first methods developed to classify coding and all variants and remain among the most frequently used in silico tools in clinical variant interpretation.

    “SIFT, PolyPhen-2, and CADD were among the first methods developed to classify coding and all variants and remain among the most frequently used in silico tools in clinical variant interpretation.5”

    From Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria (2022) · cites this paper as [5]

    The VIPdb passage on collecting tools (page not given) calls SIFT and PolyPhen pioneering variant-impact predictors. It does not extend that description to CADD or establish that the three tools are among the most frequently used in clinical variant interpretation. (LLM, conf=0.86)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Hu, Z., Yu, C., Furutsuki, M., Andreoletti, G., Ly, M., Hoskins, R., Adhikari, A. N., & Brenner, S. E.
Affiliations
University of California, Berkeley (US)
Corresponding author
Brenner, Steven E.
Venue
Human Mutation
Publisher
Wiley
Published
2019-09
Volume
40
Issue
9
Pages
1202-1214
ISSN
  • 1059-7794 (ISSN-L)
  • 1098-1004
OpenAlex
W2959541742
Cited by
37
References
180
Citations by year
2026: 5 · 2025: 3 · 2024: 7 · 2023: 4 · 2022: 4 · 2021: 5 · 2020: 7 · 2019: 2
FWCI
2.71
Type
journal article
Language
en
Open access
Locations
  • Human Mutation (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
Foundation for the National Institutes of Health (U41 HG007346, R13 HG006650)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genomics and Rare Diseases
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
Keywords
genome interpretation, precision medicine, human genetics
MeSH terms
Humans, Phenotype, Proteins, User-Computer Interface, Genetic Variation, Genome, Human, Protein Structure, Secondary, Computational Biology, Genetic Predisposition to Disease, Databases, Genetic, Precision Medicine

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review