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Somatic cancer variant curation and harmonization through consensus minimum variant level data

Overview of attention for article published in Genome Medicine, November 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (94th percentile)
  • High Attention Score compared to outputs of the same age and source (91st percentile)

Mentioned by

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2 news outlets
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46 X users

Citations

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61 Dimensions

Readers on

mendeley
134 Mendeley
Title
Somatic cancer variant curation and harmonization through consensus minimum variant level data
Published in
Genome Medicine, November 2016
DOI 10.1186/s13073-016-0367-z
Pubmed ID
Authors

Deborah I. Ritter, Sameek Roychowdhury, Angshumoy Roy, Shruti Rao, Melissa J. Landrum, Dmitriy Sonkin, Mamatha Shekar, Caleb F. Davis, Reece K. Hart, Christine Micheel, Meredith Weaver, Eliezer M. Van Allen, Donald W. Parsons, Howard L. McLeod, Michael S. Watson, Sharon E. Plon, Shashikant Kulkarni, Subha Madhavan, on behalf of the ClinGen Somatic Cancer Working Group

Abstract

To truly achieve personalized medicine in oncology, it is critical to catalog and curate cancer sequence variants for their clinical relevance. The Somatic Working Group (WG) of the Clinical Genome Resource (ClinGen), in cooperation with ClinVar and multiple cancer variant curation stakeholders, has developed a consensus set of minimal variant level data (MVLD). MVLD is a framework of standardized data elements to curate cancer variants for clinical utility. With implementation of MVLD standards, and in a working partnership with ClinVar, we aim to streamline the somatic variant curation efforts in the community and reduce redundancy and time burden for the interpretation of cancer variants in clinical practice. We developed MVLD through a consensus approach by i) reviewing clinical actionability interpretations from institutions participating in the WG, ii) conducting extensive literature search of clinical somatic interpretation schemas, and iii) survey of cancer variant web portals. A forthcoming guideline on cancer variant interpretation, from the Association of Molecular Pathology (AMP), can be incorporated into MVLD. Along with harmonizing standardized terminology for allele interpretive and descriptive fields that are collected by many databases, the MVLD includes unique fields for cancer variants such as Biomarker Class, Therapeutic Context and Effect. In addition, MVLD includes recommendations for controlled semantics and ontologies. The Somatic WG is collaborating with ClinVar to evaluate MVLD use for somatic variant submissions. ClinVar is an open and centralized repository where sequencing laboratories can report summary-level variant data with clinical significance, and ClinVar accepts cancer variant data. We expect the use of the MVLD to streamline clinical interpretation of cancer variants, enhance interoperability among multiple redundant curation efforts, and increase submission of somatic variants to ClinVar, all of which will enhance translation to clinical oncology practice.

X Demographics

X Demographics

The data shown below were collected from the profiles of 46 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 134 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 1%
Italy 1 <1%
Argentina 1 <1%
Brazil 1 <1%
Spain 1 <1%
Croatia 1 <1%
Unknown 127 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 36 27%
Other 19 14%
Student > Master 18 13%
Student > Ph. D. Student 15 11%
Professor > Associate Professor 10 7%
Other 18 13%
Unknown 18 13%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 48 36%
Agricultural and Biological Sciences 26 19%
Medicine and Dentistry 20 15%
Computer Science 7 5%
Neuroscience 2 1%
Other 11 8%
Unknown 20 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 44. 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 27 March 2019.
All research outputs
#871,503
of 23,921,147 outputs
Outputs from Genome Medicine
#168
of 1,481 outputs
Outputs of similar age
#17,271
of 314,785 outputs
Outputs of similar age from Genome Medicine
#4
of 36 outputs
Altmetric has tracked 23,921,147 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,481 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.5. This one has done well, scoring higher than 88% 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 314,785 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 94% of its contemporaries.
We're also able to compare this research output to 36 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.