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VDJviz: a versatile browser for immunogenomics data

Overview of attention for article published in BMC Genomics, June 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (92nd percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

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3 news outlets
twitter
5 X users
facebook
1 Facebook page

Citations

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27 Dimensions

Readers on

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69 Mendeley
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Title
VDJviz: a versatile browser for immunogenomics data
Published in
BMC Genomics, June 2016
DOI 10.1186/s12864-016-2799-7
Pubmed ID
Authors

Dmitriy V. Bagaev, Ivan V. Zvyagin, Ekaterina V. Putintseva, Mark Izraelson, Olga V. Britanova, Dmitriy M. Chudakov, Mikhail Shugay

Abstract

The repertoire of T- and B-cell receptor sequences encodes the antigen specificity of adaptive immunity system, determines its present state and guides its ability to mount effective response against encountered antigens in future. High throughput sequencing of immune repertoires (Rep-Seq) is a promising technique that allows to profile millions of antigen receptors of an individual in a single experiment. While a substantial number of tools for mapping and assembling Rep-Seq data were published recently, the field still lacks an intuitive and flexible tool that can be used by researchers with little or no computational background for in-depth analysis of immune repertoire profiles. Here we report VDJviz, a web tool that can be used to browse, analyze and perform quality control of Rep-Seq results generated by various pre-processing software. On a set of real data examples we show that VDJviz can be used to explore key repertoire characteristics such as spectratype, repertoire clonality, V-(D)-J recombination patterns and to identify shared clonotypes. We also demonstrate the utility of VDJviz in detection of critical Rep-Seq biases such as artificial repertoire diversity and cross-sample contamination. VDJviz is a versatile and lightweight tool that can be easily employed by biologists, immunologists and immunogeneticists for routine analysis and quality control of Rep-Seq data. The software is freely available for non-commercial purposes, and can be downloaded from: https://github.com/antigenomics/vdjviz .

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 69 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 69 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 16 23%
Student > Ph. D. Student 12 17%
Other 6 9%
Student > Master 6 9%
Student > Bachelor 5 7%
Other 9 13%
Unknown 15 22%
Readers by discipline Count As %
Agricultural and Biological Sciences 18 26%
Biochemistry, Genetics and Molecular Biology 12 17%
Immunology and Microbiology 9 13%
Medicine and Dentistry 7 10%
Nursing and Health Professions 1 1%
Other 4 6%
Unknown 18 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 27. 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 02 September 2017.
All research outputs
#1,278,772
of 23,577,761 outputs
Outputs from BMC Genomics
#240
of 10,800 outputs
Outputs of similar age
#25,299
of 354,935 outputs
Outputs of similar age from BMC Genomics
#6
of 176 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 10,800 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 97% 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 354,935 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 92% of its contemporaries.
We're also able to compare this research output to 176 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 96% of its contemporaries.