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ANGSD: Analysis of Next Generation Sequencing Data

Overview of attention for article published in BMC Bioinformatics, November 2014
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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 (96th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
3 news outlets
blogs
2 blogs
policy
1 policy source
twitter
13 X users

Citations

dimensions_citation
2138 Dimensions

Readers on

mendeley
1431 Mendeley
citeulike
1 CiteULike
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Title
ANGSD: Analysis of Next Generation Sequencing Data
Published in
BMC Bioinformatics, November 2014
DOI 10.1186/s12859-014-0356-4
Pubmed ID
Authors

Thorfinn Sand Korneliussen, Anders Albrechtsen, Rasmus Nielsen

Abstract

BackgroundHigh-throughput DNA sequencing technologies are generating vast amounts of data. Fast, flexible and memory efficient implementations are needed in order to facilitate analyses of thousands of samples simultaneously.ResultsWe present a multithreaded program suite called ANGSD. This program can calculate various summary statistics, and perform association mapping and population genetic analyses utilizing the full information in next generation sequencing data by working directly on the raw sequencing data or by using genotype likelihoods.ConclusionsThe open source c/c++ program ANGSD is available at http://www.popgen.dk/angsd. The program is tested and validated on GNU/Linux systems. The program facilitates multiple input formats including BAM and imputed beagle genotype probability files. The program allow the user to choose between combinations of existing methods and can perform analysis that is not implemented elsewhere.

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 1,431 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 13 <1%
Germany 4 <1%
Spain 3 <1%
Sweden 3 <1%
France 2 <1%
Brazil 2 <1%
Switzerland 2 <1%
Denmark 2 <1%
Mexico 2 <1%
Other 5 <1%
Unknown 1393 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 384 27%
Researcher 224 16%
Student > Master 209 15%
Student > Bachelor 128 9%
Student > Doctoral Student 77 5%
Other 160 11%
Unknown 249 17%
Readers by discipline Count As %
Agricultural and Biological Sciences 619 43%
Biochemistry, Genetics and Molecular Biology 339 24%
Environmental Science 54 4%
Computer Science 30 2%
Arts and Humanities 15 1%
Other 82 6%
Unknown 292 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 48. 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 15 March 2023.
All research outputs
#883,674
of 26,017,215 outputs
Outputs from BMC Bioinformatics
#59
of 7,793 outputs
Outputs of similar age
#11,015
of 375,779 outputs
Outputs of similar age from BMC Bioinformatics
#2
of 136 outputs
Altmetric has tracked 26,017,215 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 7,793 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.6. This one has done particularly well, scoring higher than 99% 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 375,779 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 96% of its contemporaries.
We're also able to compare this research output to 136 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 98% of its contemporaries.