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Attention Score in Context
| Title |
Optimizing multiplex SNP-based data analysis for genotyping of Mycobacterium tuberculosis isolates
|
|---|---|
| Published in |
BMC Genomics, July 2014
|
| DOI | 10.1186/1471-2164-15-572 |
| Pubmed ID | |
| Authors |
Sarah Sengstake, Nino Bablishvili, Anja Schuitema, Nino Bzekalava, Edgar Abadia, Jessica de Beer, Nona Tadumadze, Maka Akhalaia, Kiki Tuin, Nestani Tukvadze, Rusudan Aspindzelashvili, Elizabeta Bachiyska, Stefan Panaiotov, Christophe Sola, Dick van Soolingen, Paul Klatser, Richard Anthony, Indra Bergval |
| Abstract |
Multiplex ligation-dependent probe amplification (MLPA) is a powerful tool to identify genomic polymorphisms. We have previously developed a single nucleotide polymorphism (SNP) and large sequence polymorphisms (LSP)-based MLPA assay using a read out on a liquid bead array to screen for 47 genetic markers in the Mycobacterium tuberculosis genome. In our assay we obtain information regarding the Mycobacterium tuberculosis lineage and drug resistance simultaneously. Previously we called the presence or absence of a genotypic marker based on a threshold signal level. Here we present a more elaborate data analysis method to standardize and streamline the interpretation of data generated by MLPA. The new data analysis method also identifies intermediate signals in addition to classification of signals as positive and negative. Intermediate calls can be informative with respect to identifying the simultaneous presence of sensitive and resistant alleles or infection with multiple different Mycobacterium tuberculosis strains. |
X Demographics
The data shown below were collected from the profiles of 3 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 Kingdom | 2 | 67% |
| Unknown | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Colombia | 1 | 2% |
| Unknown | 58 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 22% |
| Student > Ph. D. Student | 11 | 19% |
| Student > Master | 7 | 12% |
| Other | 5 | 8% |
| Student > Bachelor | 3 | 5% |
| Other | 10 | 17% |
| Unknown | 10 | 17% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 13 | 22% |
| Medicine and Dentistry | 11 | 19% |
| Biochemistry, Genetics and Molecular Biology | 11 | 19% |
| Immunology and Microbiology | 3 | 5% |
| Computer Science | 2 | 3% |
| Other | 5 | 8% |
| Unknown | 14 | 24% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 13 March 2015.
All research outputs
#15,983,785
of 25,374,917 outputs
Outputs from BMC Genomics
#6,064
of 11,244 outputs
Outputs of similar age
#129,269
of 240,377 outputs
Outputs of similar age from BMC Genomics
#138
of 263 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 36th percentile – i.e., 36% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,244 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 45th percentile – i.e., 45% of its peers scored the same or lower than it.
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We're also able to compare this research output to 263 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.