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Defining “mutation” and “polymorphism” in the era of personal genomics

Overview of attention for article published in BMC Medical Genomics, July 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#29 of 1,234)
  • High Attention Score compared to outputs of the same age (93rd percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
15 tweeters
facebook
2 Facebook pages
wikipedia
2 Wikipedia pages

Citations

dimensions_citation
123 Dimensions

Readers on

mendeley
626 Mendeley
citeulike
3 CiteULike
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Title
Defining “mutation” and “polymorphism” in the era of personal genomics
Published in
BMC Medical Genomics, July 2015
DOI 10.1186/s12920-015-0115-z
Pubmed ID
Authors

Roshan Karki, Deep Pandya, Robert C. Elston, Cristiano Ferlini

Abstract

The growing advances in DNA sequencing tools have made analyzing the human genome cheaper and faster. While such analyses are intended to identify complex variants, related to disease susceptibility and efficacy of drug responses, they have blurred the definitions of mutation and polymorphism. In the era of personal genomics, it is critical to establish clear guidelines regarding the use of a reference genome. Nowadays DNA variants are called as differences in comparison to a reference. In a sequencing project Single Nucleotide Polymorphisms (SNPs) and DNA mutations are defined as DNA variants detectable in >1 % or <1 % of the population, respectively. The alternative use of the two terms mutation or polymorphism for the same event (a difference as compared with a reference) can lead to problems of classification. These problems can impact the accuracy of the interpretation and the functional relationship between a disease state and a genomic sequence. We propose to solve this nomenclature dilemma by defining mutations as DNA variants obtained in a paired sequencing project including the germline DNA of the same individual as a reference. Moreover, the term mutation should be accompanied by a qualifying prefix indicating whether the mutation occurs only in somatic cells (somatic mutation) or also in the germline (germline mutation). We believe this distinction in definition will help avoid confusion among researchers and support the practice of sequencing the germline and somatic tissues in parallel to classify the DNA variants thus defined as mutations.

Twitter Demographics

The data shown below were collected from the profiles of 15 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 626 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Ireland 1 <1%
Italy 1 <1%
Brazil 1 <1%
Canada 1 <1%
Spain 1 <1%
United States 1 <1%
Unknown 620 99%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 137 22%
Student > Master 113 18%
Student > Ph. D. Student 65 10%
Researcher 46 7%
Student > Doctoral Student 28 4%
Other 97 15%
Unknown 140 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 172 27%
Medicine and Dentistry 94 15%
Agricultural and Biological Sciences 64 10%
Pharmacology, Toxicology and Pharmaceutical Science 27 4%
Nursing and Health Professions 21 3%
Other 87 14%
Unknown 161 26%

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 May 2021.
All research outputs
#1,204,734
of 23,049,027 outputs
Outputs from BMC Medical Genomics
#29
of 1,234 outputs
Outputs of similar age
#16,200
of 263,108 outputs
Outputs of similar age from BMC Medical Genomics
#1
of 23 outputs
Altmetric has tracked 23,049,027 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,234 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 97% 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 263,108 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 93% of its contemporaries.
We're also able to compare this research output to 23 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.