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Recommendations for performance optimizations when using GATK3.8 and GATK4

Overview of attention for article published in BMC Bioinformatics, November 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (58th percentile)

Mentioned by

twitter
7 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
28 Mendeley
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Title
Recommendations for performance optimizations when using GATK3.8 and GATK4
Published in
BMC Bioinformatics, November 2019
DOI 10.1186/s12859-019-3169-7
Authors

Jacob R Heldenbrand, Saurabh Baheti, Matthew A Bockol, Travis M Drucker, Steven N Hart, Matthew E Hudson, Ravishankar K Iyer, Michael T Kalmbach, Katherine I Kendig, Eric W Klee, Nathan R Mattson, Eric D Wieben, Mathieu Wiepert, Derek E Wildman, Liudmila S Mainzer

Twitter Demographics

The data shown below were collected from the profiles of 7 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 28 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 25%
Student > Ph. D. Student 5 18%
Other 2 7%
Professor > Associate Professor 2 7%
Student > Master 1 4%
Other 4 14%
Unknown 7 25%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 11 39%
Agricultural and Biological Sciences 6 21%
Computer Science 3 11%
Unknown 8 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 14 November 2019.
All research outputs
#4,806,687
of 16,206,327 outputs
Outputs from BMC Bioinformatics
#2,078
of 5,867 outputs
Outputs of similar age
#122,444
of 327,830 outputs
Outputs of similar age from BMC Bioinformatics
#234
of 592 outputs
Altmetric has tracked 16,206,327 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 5,867 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 63% 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 327,830 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 62% of its contemporaries.
We're also able to compare this research output to 592 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 58% of its contemporaries.