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An integrated clinical program and crowdsourcing strategy for genomic sequencing and Mendelian disease gene discovery

Overview of attention for article published in npj Genomic Medicine, August 2018
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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 (#10 of 185)
  • High Attention Score compared to outputs of the same age (96th percentile)

Mentioned by

news
5 news outlets
twitter
72 tweeters
facebook
2 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
13 Dimensions

Readers on

mendeley
45 Mendeley
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Title
An integrated clinical program and crowdsourcing strategy for genomic sequencing and Mendelian disease gene discovery
Published in
npj Genomic Medicine, August 2018
DOI 10.1038/s41525-018-0060-9
Pubmed ID
Authors

Alireza Haghighi, Joel B. Krier, Agnes Toth-Petroczy, Christopher A. Cassa, Natasha Y. Frank, Nikkola Carmichael, Elizabeth Fieg, Andrew Bjonnes, Anwoy Mohanty, Lauren C. Briere, Sharyn Lincoln, Stephanie Lucia, Vandana A. Gupta, Onuralp Söylemez, Sheila Sutti, Kameron Kooshesh, Haiyan Qiu, Christopher J. Fay, Victoria Perroni, Jamie Valerius, Meredith Hanna, Alexander Frank, Jodie Ouahed, Scott B. Snapper, Angeliki Pantazi, Sameer S. Chopra, Ignaty Leshchiner, Nathan O. Stitziel, Anna Feldweg, Michael Mannstadt, Joseph Loscalzo, David A. Sweetser, Eric Liao, Joan M. Stoler, Catherine B. Nowak, Pedro A. Sanchez-Lara, Ophir D. Klein, Hazel Perry, Nikolaos A. Patsopoulos, Soumya Raychaudhuri, Wolfram Goessling, Robert C. Green, Christine E. Seidman, Calum A. MacRae, Shamil R. Sunyaev, Richard L. Maas, Dana Vuzman

Abstract

Despite major progress in defining the genetic basis of Mendelian disorders, the molecular etiology of many cases remains unknown. Patients with these undiagnosed disorders often have complex presentations and require treatment by multiple health care specialists. Here, we describe an integrated clinical diagnostic and research program using whole-exome and whole-genome sequencing (WES/WGS) for Mendelian disease gene discovery. This program employs specific case ascertainment parameters, a WES/WGS computational analysis pipeline that is optimized for Mendelian disease gene discovery with variant callers tuned to specific inheritance modes, an interdisciplinary crowdsourcing strategy for genomic sequence analysis, matchmaking for additional cases, and integration of the findings regarding gene causality with the clinical management plan. The interdisciplinary gene discovery team includes clinical, computational, and experimental biomedical specialists who interact to identify the genetic etiology of the disease, and when so warranted, to devise improved or novel treatments for affected patients. This program effectively integrates the clinical and research missions of an academic medical center and affords both diagnostic and therapeutic options for patients suffering from genetic disease. It may therefore be germane to other academic medical institutions engaged in implementing genomic medicine programs.

Twitter Demographics

The data shown below were collected from the profiles of 72 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 15 33%
Student > Ph. D. Student 7 16%
Other 4 9%
Student > Postgraduate 4 9%
Student > Master 3 7%
Other 7 16%
Unknown 5 11%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 16 36%
Medicine and Dentistry 8 18%
Agricultural and Biological Sciences 7 16%
Neuroscience 2 4%
Immunology and Microbiology 1 2%
Other 2 4%
Unknown 9 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 84. 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 06 October 2019.
All research outputs
#269,563
of 16,119,790 outputs
Outputs from npj Genomic Medicine
#10
of 185 outputs
Outputs of similar age
#8,733
of 278,805 outputs
Outputs of similar age from npj Genomic Medicine
#1
of 1 outputs
Altmetric has tracked 16,119,790 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 185 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 19.4. This one has done particularly well, scoring higher than 94% 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 278,805 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 96% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them