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LDkit: a parallel computing toolkit for linkage disequilibrium analysis

Overview of attention for article published in BMC Bioinformatics, October 2020
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (53rd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
8 tweeters

Readers on

mendeley
8 Mendeley
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Title
LDkit: a parallel computing toolkit for linkage disequilibrium analysis
Published in
BMC Bioinformatics, October 2020
DOI 10.1186/s12859-020-03754-5
Authors

You Tang, Zhuo Li, Chao Wang, Yuxin Liu, Helong Yu, Aoxue Wang, Yao Zhou

Twitter Demographics

The data shown below were collected from the profiles of 8 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 25%
Student > Ph. D. Student 1 13%
Student > Bachelor 1 13%
Student > Master 1 13%
Unknown 3 38%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 1 13%
Computer Science 1 13%
Agricultural and Biological Sciences 1 13%
Medicine and Dentistry 1 13%
Unknown 4 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 23 December 2020.
All research outputs
#8,970,275
of 16,520,025 outputs
Outputs from BMC Bioinformatics
#3,116
of 5,953 outputs
Outputs of similar age
#171,880
of 376,330 outputs
Outputs of similar age from BMC Bioinformatics
#234
of 476 outputs
Altmetric has tracked 16,520,025 research outputs across all sources so far. This one is in the 45th percentile – i.e., 45% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,953 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one is in the 45th percentile – i.e., 45% 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 376,330 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.
We're also able to compare this research output to 476 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.