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ASEQ: fast allele-specific studies from next-generation sequencing data

Overview of attention for article published in BMC Medical Genomics, March 2015
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)

Mentioned by

twitter
15 tweeters

Citations

dimensions_citation
41 Dimensions

Readers on

mendeley
119 Mendeley
citeulike
1 CiteULike
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Title
ASEQ: fast allele-specific studies from next-generation sequencing data
Published in
BMC Medical Genomics, March 2015
DOI 10.1186/s12920-015-0084-2
Pubmed ID
Authors

Alessandro Romanel, Sara Lago, Davide Prandi, Andrea Sboner, Francesca Demichelis

Abstract

Single base level information from next-generation sequencing (NGS) allows for the quantitative assessment of biological phenomena such as mosaicism or allele-specific features in healthy and diseased cells. Such studies often present with computationally challenging burdens that hinder genome-wide investigations across large datasets that are now becoming available through the 1,000 Genomes Project and The Cancer Genome Atlas (TCGA) initiatives.

Twitter Demographics

The data shown below were collected from the profiles of 15 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 119 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 2 2%
Italy 1 <1%
Ireland 1 <1%
Sweden 1 <1%
France 1 <1%
Unknown 113 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 34 29%
Researcher 29 24%
Student > Master 20 17%
Student > Doctoral Student 9 8%
Professor > Associate Professor 7 6%
Other 14 12%
Unknown 6 5%
Readers by discipline Count As %
Agricultural and Biological Sciences 42 35%
Biochemistry, Genetics and Molecular Biology 38 32%
Computer Science 9 8%
Medicine and Dentistry 7 6%
Immunology and Microbiology 4 3%
Other 6 5%
Unknown 13 11%

Attention Score in Context

This research output has an Altmetric Attention Score of 7. 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 26 April 2015.
All research outputs
#2,138,616
of 12,680,068 outputs
Outputs from BMC Medical Genomics
#117
of 612 outputs
Outputs of similar age
#43,667
of 217,276 outputs
Outputs of similar age from BMC Medical Genomics
#1
of 3 outputs
Altmetric has tracked 12,680,068 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 612 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has done well, scoring higher than 80% 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 217,276 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 79% of its contemporaries.
We're also able to compare this research output to 3 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