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EVA: Exome Variation Analyzer, an efficient and versatile tool for filtering strategies in medical genomics

Overview of attention for article published in BMC Bioinformatics, September 2012
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  • Above-average Attention Score compared to outputs of the same age and source (57th percentile)

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Title
EVA: Exome Variation Analyzer, an efficient and versatile tool for filtering strategies in medical genomics
Published in
BMC Bioinformatics, September 2012
DOI 10.1186/1471-2105-13-s14-s9
Pubmed ID
Authors

Sophie Coutant, Chloé Cabot, Arnaud Lefebvre, Martine Léonard, Elise Prieur-Gaston, Dominique Campion, Thierry Lecroq, Hélène Dauchel

Abstract

Whole exome sequencing (WES) has become the strategy of choice to identify a coding allelic variant for a rare human monogenic disorder. This approach is a revolution in medical genetics history, impacting both fundamental research, and diagnostic methods leading to personalized medicine. A plethora of efficient algorithms has been developed to ensure the variant discovery. They generally lead to ~20,000 variations that have to be narrow down to find the potential pathogenic allelic variant(s) and the affected gene(s). For this purpose, commonly adopted procedures which implicate various filtering strategies have emerged: exclusion of common variations, type of the allelics variants, pathogenicity effect prediction, modes of inheritance and multiple individuals for exome comparison. To deal with the expansion of WES in medical genomics individual laboratories, new convivial and versatile software tools have to implement these filtering steps. Non-programmer biologists have to be autonomous combining themselves different filtering criteria and conduct a personal strategy depending on their assumptions and study design.

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 84 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
France 1 1%
Italy 1 1%
Australia 1 1%
Netherlands 1 1%
Sweden 1 1%
Brazil 1 1%
Spain 1 1%
United Kingdom 1 1%
Other 0 0%
Unknown 74 88%

Demographic breakdown

Readers by professional status Count As %
Researcher 25 30%
Student > Ph. D. Student 17 20%
Student > Master 12 14%
Student > Bachelor 6 7%
Student > Doctoral Student 4 5%
Other 11 13%
Unknown 9 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 37 44%
Biochemistry, Genetics and Molecular Biology 9 11%
Medicine and Dentistry 8 10%
Computer Science 5 6%
Neuroscience 3 4%
Other 7 8%
Unknown 15 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 April 2013.
All research outputs
#12,670,768
of 22,684,168 outputs
Outputs from BMC Bioinformatics
#3,620
of 7,252 outputs
Outputs of similar age
#87,865
of 169,039 outputs
Outputs of similar age from BMC Bioinformatics
#41
of 96 outputs
Altmetric has tracked 22,684,168 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,252 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 48th percentile – i.e., 48% of its peers scored the same or lower than it.
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 169,039 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 96 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 57% of its contemporaries.