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VPA: an R tool for analyzing sequencing variants with user-specified frequency pattern

Overview of attention for article published in BMC Research Notes, January 2012
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters

Readers on

mendeley
27 Mendeley
citeulike
2 CiteULike
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Title
VPA: an R tool for analyzing sequencing variants with user-specified frequency pattern
Published in
BMC Research Notes, January 2012
DOI 10.1186/1756-0500-5-31
Pubmed ID
Authors

Qiang Hu, Dan Wang, Li Yan, Hua Zhao, Song Liu

Abstract

The massive amounts of genetic variant generated by the next generation sequencing systems demand the development of effective computational tools for variant prioritization.

Twitter Demographics

The data shown below were collected from the profiles of 2 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 27 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 2 7%
Spain 2 7%
Unknown 23 85%

Demographic breakdown

Readers by professional status Count As %
Researcher 9 33%
Student > Ph. D. Student 6 22%
Professor 3 11%
Professor > Associate Professor 2 7%
Student > Master 2 7%
Other 3 11%
Unknown 2 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 41%
Medicine and Dentistry 6 22%
Biochemistry, Genetics and Molecular Biology 5 19%
Computer Science 1 4%
Social Sciences 1 4%
Other 1 4%
Unknown 2 7%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 10 July 2012.
All research outputs
#9,613,455
of 12,519,627 outputs
Outputs from BMC Research Notes
#1,791
of 2,804 outputs
Outputs of similar age
#145,382
of 217,277 outputs
Outputs of similar age from BMC Research Notes
#145
of 229 outputs
Altmetric has tracked 12,519,627 research outputs across all sources so far. This one is in the 19th percentile – i.e., 19% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,804 research outputs from this source. They receive a mean Attention Score of 4.4. This one is in the 30th percentile – i.e., 30% 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 217,277 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 229 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.