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ECNano: A cost-effective workflow for target enrichment sequencing and accurate variant calling on 4800 clinically significant genes using a single MinION flowcell

Overview of attention for article published in BMC Medical Genomics, March 2022
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
28 Mendeley
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Title
ECNano: A cost-effective workflow for target enrichment sequencing and accurate variant calling on 4800 clinically significant genes using a single MinION flowcell
Published in
BMC Medical Genomics, March 2022
DOI 10.1186/s12920-022-01190-3
Pubmed ID
Authors

Amy Wing-Sze Leung, Henry Chi-Ming Leung, Chak-Lim Wong, Zhen-Xian Zheng, Wui-Wang Lui, Ho-Ming Luk, Ivan Fai-Man Lo, Ruibang Luo, Tak-Wah Lam

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 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 %
Student > Ph. D. Student 4 14%
Researcher 4 14%
Professor > Associate Professor 3 11%
Professor 2 7%
Other 2 7%
Other 3 11%
Unknown 10 36%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 9 32%
Engineering 2 7%
Medicine and Dentistry 2 7%
Environmental Science 1 4%
Agricultural and Biological Sciences 1 4%
Other 2 7%
Unknown 11 39%
Attention Score in Context

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 13 April 2022.
All research outputs
#7,115,080
of 23,881,329 outputs
Outputs from BMC Medical Genomics
#324
of 1,268 outputs
Outputs of similar age
#141,440
of 443,858 outputs
Outputs of similar age from BMC Medical Genomics
#6
of 40 outputs
Altmetric has tracked 23,881,329 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 1,268 research outputs from this source. They receive a mean Attention Score of 4.7. This one has gotten more attention than average, scoring higher than 74% 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 443,858 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 67% of its contemporaries.
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 has done well, scoring higher than 87% of its contemporaries.