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Flexible metagenome analysis using the MGX framework

Overview of attention for article published in Microbiome, April 2018
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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 (87th percentile)
  • Average Attention Score compared to outputs of the same age and source

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1 blog
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8 X users
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2 Wikipedia pages

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51 Mendeley
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Title
Flexible metagenome analysis using the MGX framework
Published in
Microbiome, April 2018
DOI 10.1186/s40168-018-0460-1
Pubmed ID
Authors

Sebastian Jaenicke, Stefan P. Albaum, Patrick Blumenkamp, Burkhard Linke, Jens Stoye, Alexander Goesmann

Abstract

The characterization of microbial communities based on sequencing and analysis of their genetic information has become a popular approach also referred to as metagenomics; in particular, the recent advances in sequencing technologies have enabled researchers to study even the most complex communities. Metagenome analysis, the assignment of sequences to taxonomic and functional entities, however, remains a tedious task: large amounts of data need to be processed. There are a number of approaches addressing particular aspects, but scientific questions are often too specific to be answered by a general-purpose method. We present MGX, a flexible and extensible client/server-framework for the management and analysis of metagenomic datasets; MGX features a comprehensive set of adaptable workflows required for taxonomic and functional metagenome analysis, combined with an intuitive and easy-to-use graphical user interface offering customizable result visualizations. At the same time, MGX allows to include own data sources and devise custom analysis pipelines, thus enabling researchers to perform basic as well as highly specific analyses within a single application. With MGX, we provide a novel metagenome analysis platform giving researchers access to the most recent analysis tools. MGX covers taxonomic and functional metagenome analysis, statistical evaluation, and a wide range of visualizations easing data interpretation. Its default taxonomic classification pipeline provides equivalent or superior results in comparison to existing tools.

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 25%
Student > Ph. D. Student 10 20%
Student > Master 8 16%
Student > Bachelor 3 6%
Student > Postgraduate 2 4%
Other 6 12%
Unknown 9 18%
Readers by discipline Count As %
Agricultural and Biological Sciences 17 33%
Biochemistry, Genetics and Molecular Biology 11 22%
Computer Science 5 10%
Medicine and Dentistry 2 4%
Environmental Science 1 2%
Other 2 4%
Unknown 13 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 19. 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 04 April 2023.
All research outputs
#1,823,823
of 24,093,053 outputs
Outputs from Microbiome
#713
of 1,593 outputs
Outputs of similar age
#39,723
of 330,281 outputs
Outputs of similar age from Microbiome
#33
of 57 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,593 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 39.4. This one has gotten more attention than average, scoring higher than 55% 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 330,281 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 87% of its contemporaries.
We're also able to compare this research output to 57 others from the same source and published within six weeks on either side of this one. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.