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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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27 Mendeley
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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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

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 4 15%
Computer Science 2 7%
Social Sciences 1 4%
Other 1 4%
Unknown 2 7%
Attention Score in Context

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
#17,654,408
of 22,661,413 outputs
Outputs from BMC Research Notes
#2,819
of 4,248 outputs
Outputs of similar age
#190,149
of 243,441 outputs
Outputs of similar age from BMC Research Notes
#58
of 79 outputs
Altmetric has tracked 22,661,413 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 4,248 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one is in the 29th percentile – i.e., 29% 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 243,441 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 19th percentile – i.e., 19% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 79 others from the same source and published within six weeks on either side of this one. This one is in the 25th percentile – i.e., 25% of its contemporaries scored the same or lower than it.