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Attention Score in Context
| Title |
swga: A primer design toolkit for selective whole genome amplification
|
|---|---|
| Published in |
Bioinformatics, February 2017
|
| DOI | 10.1093/bioinformatics/btx118 |
| Pubmed ID | |
| Authors |
Erik L. Clarke, Sesh A. Sundararaman, Stephanie N. Seifert, Frederic D. Bushman, Beatrice H. Hahn, Dustin Brisson |
| Abstract |
Population genomic analyses are often hindered by difficulties in obtaining sufficient numbers of genomes for analysis by DNA sequencing. Selective whole-genome amplification (SWGA) provides an efficient approach to amplify microbial genomes from complex backgrounds for sequence acquisition. However, the process of designing sets of primers for this method has many degrees of freedom and would benefit from an automated process to evaluate the vast number of potential primer sets. Here we present swga, a program that identifies primer sets for selective whole-genome amplification and evaluates them for efficiency and selectivity.We used swga to design and test primer sets for the selective amplification ofWolbachia pipientis genomic DNA from infected Drosophila melanogaster and Mycobacterium tuberculosis from human blood. We identify primer sets that successfully amplify each against their backgrounds and describe a general method for using swga for arbitrary targets. In addition, we describe characteristics of primer sets that correlate with successful amplification, and present guidelines for implementation of SWGA to detect new targets. Source code and documentation are freely available on https://www.github.com/eclarke/swga . The program is implemented in Python and C and licensed under the GNU Public License. [email protected]. Supplementary data are available at Bioinformatics online. |
X Demographics
The data shown below were collected from the profiles of 4 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 | 1 | 25% |
| United Kingdom | 1 | 25% |
| Germany | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 75% |
| Scientists | 1 | 25% |
Mendeley readers
The data shown below were compiled from readership statistics for 98 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Sweden | 1 | 1% |
| Unknown | 97 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 22 | 22% |
| Student > Ph. D. Student | 21 | 21% |
| Student > Master | 14 | 14% |
| Student > Doctoral Student | 7 | 7% |
| Professor | 5 | 5% |
| Other | 15 | 15% |
| Unknown | 14 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 36 | 37% |
| Agricultural and Biological Sciences | 25 | 26% |
| Medicine and Dentistry | 7 | 7% |
| Immunology and Microbiology | 4 | 4% |
| Engineering | 3 | 3% |
| Other | 7 | 7% |
| Unknown | 16 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 43. 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 12 November 2021.
All research outputs
#966,643
of 25,377,790 outputs
Outputs from Bioinformatics
#260
of 12,810 outputs
Outputs of similar age
#20,024
of 325,404 outputs
Outputs of similar age from Bioinformatics
#10
of 195 outputs
Altmetric has tracked 25,377,790 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 12,810 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.0. This one has done particularly well, scoring higher than 97% 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 325,404 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 93% of its contemporaries.
We're also able to compare this research output to 195 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 95% of its contemporaries.