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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
  • Among the highest-scoring outputs from this source (#25 of 408)
  • High Attention Score compared to outputs of the same age (96th percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

news
5 news outlets
twitter
59 X users
facebook
2 Facebook pages
googleplus
1 Google+ user

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
64 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, Undiagnosed Diseases Network, Brigham and Women’s Hospital FaceBase Project, Brigham Genomic Medicine (BGM)

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.

X Demographics

X Demographics

The data shown below were collected from the profiles of 59 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 64 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 64 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 25%
Student > Ph. D. Student 7 11%
Other 5 8%
Student > Bachelor 4 6%
Student > Doctoral Student 4 6%
Other 13 20%
Unknown 15 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 18 28%
Medicine and Dentistry 10 16%
Agricultural and Biological Sciences 8 13%
Business, Management and Accounting 2 3%
Neuroscience 2 3%
Other 4 6%
Unknown 20 31%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 71. 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
#610,432
of 25,595,500 outputs
Outputs from npj Genomic Medicine
#25
of 408 outputs
Outputs of similar age
#12,932
of 341,813 outputs
Outputs of similar age from npj Genomic Medicine
#5
of 12 outputs
Altmetric has tracked 25,595,500 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 408 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 18.4. 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 341,813 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 12 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.