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Development of a Comprehensive Sequencing Assay for Inherited Cardiac Condition Genes

Overview of attention for article published in Journal of Cardiovascular Translational Research, February 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#2 of 576)
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

news
20 news outlets
blogs
1 blog
twitter
50 X users
facebook
6 Facebook pages

Citations

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77 Dimensions

Readers on

mendeley
119 Mendeley
Title
Development of a Comprehensive Sequencing Assay for Inherited Cardiac Condition Genes
Published in
Journal of Cardiovascular Translational Research, February 2016
DOI 10.1007/s12265-016-9673-5
Pubmed ID
Authors

Chee Jian Pua, Jaydutt Bhalshankar, Kui Miao, Roddy Walsh, Shibu John, Shi Qi Lim, Kingsley Chow, Rachel Buchan, Bee Yong Soh, Pei Min Lio, Jaclyn Lim, Sebastian Schafer, Jing Quan Lim, Patrick Tan, Nicola Whiffin, Paul J. Barton, James S. Ware, Stuart A. Cook

Abstract

Inherited cardiac conditions (ICCs) are characterised by marked genetic and allelic heterogeneity and require extensive sequencing for genetic characterisation. We iteratively optimised a targeted gene capture panel for ICCs that includes disease-causing, putatively pathogenic, research and phenocopy genes (n = 174 genes). We achieved high coverage of the target region on both MiSeq (>99.8 % at ≥20× read depth, n = 12) and NextSeq (>99.9 % at ≥20×, n = 48) platforms with 100 % sensitivity and precision for single nucleotide variants and indels across the protein-coding target on the MiSeq. In the final assay, 40 out of 43 established ICC genes informative in clinical practice achieved complete coverage (100 % at ≥20×). By comparison, whole exome sequencing (WES; ∼80×), deep WES (∼500×) and whole genome sequencing (WGS; ∼70×) had poorer performance (88.1, 99.2 and 99.3 % respectively at ≥20×) across the ICC target. The assay described here delivers highly accurate and affordable sequencing of ICC genes, complemented by accessible cloud-based computation and informatics. See Editorial in this issue (DOI: 10.1007/s12265-015-9667-8 ).

X Demographics

X Demographics

The data shown below were collected from the profiles of 50 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 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 <1%
Unknown 118 99%

Demographic breakdown

Readers by professional status Count As %
Researcher 24 20%
Student > Ph. D. Student 22 18%
Student > Bachelor 15 13%
Other 13 11%
Student > Master 11 9%
Other 20 17%
Unknown 14 12%
Readers by discipline Count As %
Medicine and Dentistry 33 28%
Biochemistry, Genetics and Molecular Biology 29 24%
Agricultural and Biological Sciences 25 21%
Engineering 3 3%
Computer Science 2 2%
Other 12 10%
Unknown 15 13%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 195. 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 29 June 2021.
All research outputs
#168,006
of 22,849,304 outputs
Outputs from Journal of Cardiovascular Translational Research
#2
of 576 outputs
Outputs of similar age
#3,232
of 297,955 outputs
Outputs of similar age from Journal of Cardiovascular Translational Research
#1
of 12 outputs
Altmetric has tracked 22,849,304 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 576 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 99% 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 297,955 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% of its contemporaries.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 91% of its contemporaries.