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X Demographics
Mendeley readers
Attention Score in Context
| Title |
MetaSee: An Interactive and Extendable Visualization Toolbox for Metagenomic Sample Analysis and Comparison
|
|---|---|
| Published in |
PLOS ONE, November 2012
|
| DOI | 10.1371/journal.pone.0048998 |
| Pubmed ID | |
| Authors |
Baoxing Song, Xiaoquan Su, Jian Xu, Kang Ning |
| Abstract |
The NGS (next generation sequencing)-based metagenomic data analysis is becoming the mainstream for the study of microbial communities. Faced with a large amount of data in metagenomic research, effective data visualization is important for scientists to effectively explore, interpret and manipulate such rich information. The visualization of the metagenomic data, especially multi-sample data, is one of the most critical challenges. The different data sample sources, sequencing approaches and heterogeneous data formats make robust and seamless data visualization difficult. Moreover, researchers have different focuses on metagenomic studies: taxonomical or functional, sample-centric or genome-centric, single sample or multiple samples, etc. However, current efforts in metagenomic data visualization cannot fulfill all of these needs, and it is extremely hard to organize all of these visualization effects in a systematic manner. An extendable, interactive visualization tool would be the method of choice to fulfill all of these visualization needs. In this paper, we have present MetaSee, an extendable toolbox that facilitates the interactive visualization of metagenomic samples of interests. The main components of MetaSee include: (I) a core visualization engine that is composed of different views for comparison of multiple samples: Global view, Phylogenetic view, Sample view and Taxa view, as well as link-out for more in-depth analysis; (II) front-end user interface with real metagenomic models that connect to the above core visualization engine and (III) open-source portal for the development of plug-ins for MetaSee. This integrative visualization tool not only provides the visualization effects, but also enables researchers to perform in-depth analysis of the metagenomic samples of interests. Moreover, its open-source portal allows for the design of plug-ins for MetaSee, which would facilitate the development of any additional visualization effects. |
X Demographics
The data shown below were collected from the profiles of 12 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 5 | 42% |
| United Kingdom | 1 | 8% |
| Peru | 1 | 8% |
| Germany | 1 | 8% |
| Canada | 1 | 8% |
| Unknown | 3 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 7 | 58% |
| Members of the public | 4 | 33% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 3% |
| Canada | 2 | 2% |
| Spain | 2 | 2% |
| Sweden | 1 | <1% |
| India | 1 | <1% |
| Brazil | 1 | <1% |
| Belgium | 1 | <1% |
| Germany | 1 | <1% |
| France | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 89 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 31 | 30% |
| Student > Ph. D. Student | 26 | 25% |
| Student > Master | 12 | 12% |
| Student > Doctoral Student | 7 | 7% |
| Student > Bachelor | 6 | 6% |
| Other | 13 | 13% |
| Unknown | 8 | 8% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 52 | 50% |
| Biochemistry, Genetics and Molecular Biology | 13 | 13% |
| Environmental Science | 6 | 6% |
| Computer Science | 4 | 4% |
| Immunology and Microbiology | 3 | 3% |
| Other | 12 | 12% |
| Unknown | 13 | 13% |
Attention Score in Context
This research output has an Altmetric Attention Score of 6. 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 05 August 2013.
All research outputs
#5,315,001
of 24,953,268 outputs
Outputs from PLOS ONE
#83,637
of 216,204 outputs
Outputs of similar age
#37,898
of 188,560 outputs
Outputs of similar age from PLOS ONE
#1,153
of 4,919 outputs
Altmetric has tracked 24,953,268 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 216,204 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.7. This one has gotten more attention than average, scoring higher than 60% 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 188,560 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 77% of its contemporaries.
We're also able to compare this research output to 4,919 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.