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GAVIN: Gene-Aware Variant INterpretation for medical sequencing

Overview of attention for article published in Genome Biology (Online Edition), January 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (73rd percentile)

Mentioned by

twitter
4 tweeters
patent
1 patent

Citations

dimensions_citation
44 Dimensions

Readers on

mendeley
135 Mendeley
citeulike
1 CiteULike
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Title
GAVIN: Gene-Aware Variant INterpretation for medical sequencing
Published in
Genome Biology (Online Edition), January 2017
DOI 10.1186/s13059-016-1141-7
Pubmed ID
Authors

K. Joeri van der Velde, Eddy N. de Boer, Cleo C. van Diemen, Birgit Sikkema-Raddatz, Kristin M. Abbott, Alain Knopperts, Lude Franke, Rolf H. Sijmons, Tom J. de Koning, Cisca Wijmenga, Richard J. Sinke, Morris A. Swertz

Abstract

We present Gene-Aware Variant INterpretation (GAVIN), a new method that accurately classifies variants for clinical diagnostic purposes. Classifications are based on gene-specific calibrations of allele frequencies from the ExAC database, likely variant impact using SnpEff, and estimated deleteriousness based on CADD scores for >3000 genes. In a benchmark on 18 clinical gene sets, we achieve a sensitivity of 91.4% and a specificity of 76.9%. This accuracy is unmatched by 12 other tools. We provide GAVIN as an online MOLGENIS service to annotate VCF files and as an open source executable for use in bioinformatic pipelines. It can be found at http://molgenis.org/gavin .

Twitter Demographics

The data shown below were collected from the profiles of 4 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 135 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
Unknown 134 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 38 28%
Researcher 22 16%
Student > Master 16 12%
Student > Bachelor 13 10%
Student > Postgraduate 9 7%
Other 15 11%
Unknown 22 16%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 42 31%
Agricultural and Biological Sciences 32 24%
Medicine and Dentistry 20 15%
Computer Science 8 6%
Pharmacology, Toxicology and Pharmaceutical Science 2 1%
Other 7 5%
Unknown 24 18%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 January 2022.
All research outputs
#5,149,896
of 20,983,497 outputs
Outputs from Genome Biology (Online Edition)
#2,729
of 3,996 outputs
Outputs of similar age
#100,911
of 387,490 outputs
Outputs of similar age from Genome Biology (Online Edition)
#2
of 2 outputs
Altmetric has tracked 20,983,497 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,996 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 387,490 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 73% of its contemporaries.
We're also able to compare this research output to 2 others from the same source and published within six weeks on either side of this one.