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Mutation Detection in Patients with Retinal Dystrophies Using Targeted Next Generation Sequencing

Overview of attention for article published in PLOS ONE, January 2016
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Article details
Title
Mutation Detection in Patients with Retinal Dystrophies Using Targeted Next Generation Sequencing
Published in
PLOS ONE, January 2016
DOI 10.1371/journal.pone.0145951
Pubmed ID
Authors
Abstract

Retinal dystrophies (RD) constitute a group of blinding diseases that are characterized by clinical variability and pronounced genetic heterogeneity. The different nonsyndromic and syndromic forms of RD can be attributed to mutations in more than 200 genes. Consequently, next generation sequencing (NGS) technologies are among the most promising approaches to identify mutations in RD. We screened a large cohort of patients comprising 89 independent cases and families with various subforms of RD applying different NGS platforms. While mutation screening in 50 cases was performed using a RD gene capture panel, 47 cases were analyzed using whole exome sequencing. One family was analyzed using whole genome sequencing. A detection rate of 61% was achieved including mutations in 34 known and two novel RD genes. A total of 69 distinct mutations were identified, including 39 novel mutations. Notably, genetic findings in several families were not consistent with the initial clinical diagnosis. Clinical reassessment resulted in refinement of the clinical diagnosis in some of these families and confirmed the broad clinical spectrum associated with mutations in RD genes.

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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 123 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
South Africa 1 <1%
Unknown 122 99%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Researcher 23 19%
Student > Ph. D. Student 20 16%
Student > Bachelor 14 11%
Student > Master 13 11%
Other 8 7%
Other 13 11%
Unknown 32 26%
Readers by discipline
Readers by discipline Count As %
Medicine and Dentistry 28 23%
Biochemistry, Genetics and Molecular Biology 27 22%
Agricultural and Biological Sciences 16 13%
Computer Science 3 2%
Neuroscience 2 2%
Other 7 6%
Unknown 40 33%
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 15 January 2016.
All research outputs
#28,510,461
of 34,286,339 outputs
Outputs from PLOS ONE
#183,451
of 224,169 outputs
Outputs of similar age
#352,278
of 450,518 outputs
Outputs of similar age from PLOS ONE
#4,168
of 5,091 outputs
Altmetric has tracked 34,286,339 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 224,169 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 17.1. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
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We're also able to compare this research output to 5,091 others from the same source and published within six weeks on either side of this one. This one is in the 10th percentile – i.e., 10% of its contemporaries scored the same or lower than it.