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An adaptive method of defining negative mutation status for multi-sample comparison using next-generation sequencing

Overview of attention for article published in BMC Medical Genomics, December 2021
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1 X user

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3 Mendeley
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Title
An adaptive method of defining negative mutation status for multi-sample comparison using next-generation sequencing
Published in
BMC Medical Genomics, December 2021
DOI 10.1186/s12920-021-00880-8
Pubmed ID
Authors

Nicholas Hutson, Fenglin Zhan, James Graham, Mitsuko Murakami, Han Zhang, Sujana Ganaparti, Qiang Hu, Li Yan, Changxing Ma, Song Liu, Jun Xie, Lei Wei

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 3 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 1 33%
Unknown 2 67%
Readers by discipline Count As %
Unknown 3 100%
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 03 December 2021.
All research outputs
#20,710,927
of 23,310,485 outputs
Outputs from BMC Medical Genomics
#1,030
of 1,252 outputs
Outputs of similar age
#416,376
of 509,863 outputs
Outputs of similar age from BMC Medical Genomics
#28
of 40 outputs
Altmetric has tracked 23,310,485 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,252 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 1st percentile – i.e., 1% 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 509,863 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 40 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.