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Clinical implications and considerations for evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines

Overview of attention for article published in Genome Medicine, December 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 (76th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
12 tweeters

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
67 Mendeley
Title
Clinical implications and considerations for evaluation of in silico algorithms for use with ACMG/AMP clinical variant interpretation guidelines
Published in
Genome Medicine, December 2017
DOI 10.1186/s13073-017-0508-z
Pubmed ID
Authors

Lora J. H. Bean, Madhuri R. Hegde

Abstract

Clinical genetics laboratories have recently adopted guidelines for the interpretation of sequence variants set by the American College of Medical Genetics (ACMG) and Association for Molecular Pathology (AMP). The use of in silico algorithms to predict whether amino acid substitutions result in human disease is inconsistent across clinical laboratories. The clinical genetics community must carefully consider how in silico predictions can be incorporated into variant interpretation in clinical practice.Please see related Research article: https://doi.org/10.1186/s13059-017-1353-5.

Twitter Demographics

The data shown below were collected from the profiles of 12 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 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 20 30%
Other 11 16%
Student > Ph. D. Student 7 10%
Student > Master 7 10%
Student > Bachelor 5 7%
Other 8 12%
Unknown 9 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 37%
Agricultural and Biological Sciences 11 16%
Medicine and Dentistry 10 15%
Computer Science 4 6%
Pharmacology, Toxicology and Pharmaceutical Science 1 1%
Other 2 3%
Unknown 14 21%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 20 April 2018.
All research outputs
#2,170,377
of 12,829,119 outputs
Outputs from Genome Medicine
#521
of 922 outputs
Outputs of similar age
#88,667
of 384,783 outputs
Outputs of similar age from Genome Medicine
#30
of 43 outputs
Altmetric has tracked 12,829,119 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 922 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.7. This one is in the 43rd percentile – i.e., 43% 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 384,783 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 76% of its contemporaries.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 30th percentile – i.e., 30% of its contemporaries scored the same or lower than it.