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Vcfanno: fast, flexible annotation of genetic variants

Overview of attention for article published in Genome Biology, June 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

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25 X users
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2 patents

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175 Mendeley
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5 CiteULike
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Title
Vcfanno: fast, flexible annotation of genetic variants
Published in
Genome Biology, June 2016
DOI 10.1186/s13059-016-0973-5
Pubmed ID
Authors

Brent S. Pedersen, Ryan M. Layer, Aaron R. Quinlan

Abstract

The integration of genome annotations is critical to the identification of genetic variants that are relevant to studies of disease or other traits. However, comprehensive variant annotation with diverse file formats is difficult with existing methods. Here we describe vcfanno, which flexibly extracts and summarizes attributes from multiple annotation files and integrates the annotations within the INFO column of the original VCF file. By leveraging a parallel "chromosome sweeping" algorithm, we demonstrate substantial performance gains by annotating ~85,000 variants per second with 50 attributes from 17 commonly used genome annotation resources. Vcfanno is available at https://github.com/brentp/vcfanno under the MIT license.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 25 X users who shared this research output. Click here to find out more about how the information was compiled.
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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 175 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 <1%
France 1 <1%
Sweden 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
Egypt 1 <1%
Japan 1 <1%
United States 1 <1%
Unknown 167 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 59 34%
Student > Ph. D. Student 32 18%
Student > Master 19 11%
Student > Bachelor 9 5%
Student > Doctoral Student 6 3%
Other 20 11%
Unknown 30 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 62 35%
Agricultural and Biological Sciences 52 30%
Computer Science 10 6%
Medicine and Dentistry 8 5%
Neuroscience 3 2%
Other 8 5%
Unknown 32 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 20. 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 30 July 2019.
All research outputs
#1,959,315
of 26,542,140 outputs
Outputs from Genome Biology
#1,593
of 4,631 outputs
Outputs of similar age
#33,138
of 356,836 outputs
Outputs of similar age from Genome Biology
#37
of 83 outputs
Altmetric has tracked 26,542,140 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 4,631 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.2. This one has gotten more attention than average, scoring higher than 65% of its peers.
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 356,836 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 83 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.