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Exome sequencing in mostly consanguineous Arab families with neurologic disease provides a high potential molecular diagnosis rate

Overview of attention for article published in BMC Medical Genomics, July 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (74th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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Citations

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82 Mendeley
Title
Exome sequencing in mostly consanguineous Arab families with neurologic disease provides a high potential molecular diagnosis rate
Published in
BMC Medical Genomics, July 2016
DOI 10.1186/s12920-016-0208-3
Pubmed ID
Authors

Wu-Lin Charng, Ender Karaca, Zeynep Coban Akdemir, Tomasz Gambin, Mehmed M. Atik, Shen Gu, Jennifer E. Posey, Shalini N. Jhangiani, Donna M. Muzny, Harsha Doddapaneni, Jianhong Hu, Eric Boerwinkle, Richard A. Gibbs, Jill A. Rosenfeld, Hong Cui, Fan Xia, Kandamurugu Manickam, Yaping Yang, Eissa A. Faqeih, Ali Al Asmari, Mohammed A. M. Saleh, Ayman W. El-Hattab, James R. Lupski

Abstract

Neurodevelopment is orchestrated by a wide range of genes, and the genetic causes of neurodevelopmental disorders are thus heterogeneous. We applied whole exome sequencing (WES) for molecular diagnosis and in silico analysis to identify novel disease gene candidates in a cohort from Saudi Arabia with primarily Mendelian neurologic diseases. We performed WES in 31 mostly consanguineous Arab families and analyzed both single nucleotide and copy number variants (CNVs) from WES data. Interaction/expression network and pathway analyses, as well as paralog studies were utilized to investigate potential pathogenicity and disease association of novel candidate genes. Additional cases for candidate genes were identified through the clinical WES database at Baylor Miraca Genetics Laboratories and GeneMatcher. We found known pathogenic or novel variants in known disease genes with phenotypic expansion in 6 families, disease-associated CNVs in 2 families, and 12 novel disease gene candidates in 11 families, including KIF5B, GRM7, FOXP4, MLLT1, and KDM2B. Overall, a potential molecular diagnosis was provided by variants in known disease genes in 17 families (54.8 %) and by novel candidate disease genes in an additional 11 families, making the potential molecular diagnostic rate ~90 %. Molecular diagnostic rate from WES is improved by exome-predicted CNVs. Novel candidate disease gene discovery is facilitated by paralog studies and through the use of informatics tools and available databases to identify additional evidence for pathogenicity. Not applicable.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 82 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 82 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 15%
Student > Bachelor 10 12%
Researcher 9 11%
Student > Master 8 10%
Student > Doctoral Student 4 5%
Other 15 18%
Unknown 24 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 25 30%
Medicine and Dentistry 11 13%
Agricultural and Biological Sciences 7 9%
Computer Science 3 4%
Psychology 2 2%
Other 9 11%
Unknown 25 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 22 October 2019.
All research outputs
#5,444,238
of 22,914,829 outputs
Outputs from BMC Medical Genomics
#244
of 1,226 outputs
Outputs of similar age
#92,410
of 363,189 outputs
Outputs of similar age from BMC Medical Genomics
#5
of 19 outputs
Altmetric has tracked 22,914,829 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,226 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done well, scoring higher than 80% 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 363,189 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 74% of its contemporaries.
We're also able to compare this research output to 19 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.