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KvarQ: targeted and direct variant calling from fastq reads of bacterial genomes

Overview of attention for article published in BMC Genomics, January 2014
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (75th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

twitter
4 tweeters
patent
1 patent

Citations

dimensions_citation
81 Dimensions

Readers on

mendeley
152 Mendeley
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Title
KvarQ: targeted and direct variant calling from fastq reads of bacterial genomes
Published in
BMC Genomics, January 2014
DOI 10.1186/1471-2164-15-881
Pubmed ID
Authors

Andreas Steiner, David Stucki, Mireia Coscolla, Sonia Borrell, Sebastien Gagneux

Abstract

High-throughput DNA sequencing produces vast amounts of data, with millions of short reads that usually have to be mapped to a reference genome or newly assembled. Both reference-based mapping and de novo assembly are computationally intensive, generating large intermediary data files, and thus require bioinformatics skills that are often lacking in the laboratories producing the data. Moreover, many research and practical applications in microbiology require only a small fraction of the whole genome data.

Twitter Demographics

The data shown below were collected from the profiles of 4 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 152 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 <1%
Australia 1 <1%
Sweden 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
United States 1 <1%
Unknown 146 96%

Demographic breakdown

Readers by professional status Count As %
Researcher 39 26%
Student > Master 31 20%
Student > Ph. D. Student 23 15%
Student > Bachelor 11 7%
Other 10 7%
Other 22 14%
Unknown 16 11%
Readers by discipline Count As %
Agricultural and Biological Sciences 51 34%
Medicine and Dentistry 20 13%
Biochemistry, Genetics and Molecular Biology 18 12%
Immunology and Microbiology 15 10%
Computer Science 12 8%
Other 13 9%
Unknown 23 15%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 21 April 2020.
All research outputs
#4,622,968
of 17,489,191 outputs
Outputs from BMC Genomics
#2,122
of 9,314 outputs
Outputs of similar age
#52,228
of 218,501 outputs
Outputs of similar age from BMC Genomics
#1
of 10 outputs
Altmetric has tracked 17,489,191 research outputs across all sources so far. This one has received more attention than most of these and is in the 73rd percentile.
So far Altmetric has tracked 9,314 research outputs from this source. They receive a mean Attention Score of 4.4. This one has done well, scoring higher than 76% 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 218,501 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 10 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