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Inferring patient to patient transmission of Mycobacterium tuberculosisfrom whole genome sequencing data

Overview of attention for article published in BMC Infectious Diseases, February 2013
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  • Good Attention Score compared to outputs of the same age (68th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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6 X users
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1 Google+ user

Citations

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170 Dimensions

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230 Mendeley
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2 CiteULike
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Title
Inferring patient to patient transmission of Mycobacterium tuberculosisfrom whole genome sequencing data
Published in
BMC Infectious Diseases, February 2013
DOI 10.1186/1471-2334-13-110
Pubmed ID
Authors

Josephine M Bryant, Anita C Schürch, Henk van Deutekom, Simon R Harris, Jessica L de Beer, Victor de Jager, Kristin Kremer, Sacha A F T van Hijum, Roland J Siezen, Martien Borgdorff, Stephen D Bentley, Julian Parkhill, Dick van Soolingen

Abstract

BACKGROUND: Mycobacterium tuberculosis is characterised by limited genomic diversity, which makes the application of whole genome sequencing particularly attractive for clinical and epidemiological investigation. However, in order to confidently infer transmission events, an accurate knowledge of the rate of change in the genome over relevant timescales is required. METHODS: We attempted to estimate a molecular clock by sequencing 199 isolates from epidemiologically linked tuberculosis cases, collected in the Netherlands spanning almost 16 years. RESULTS: Multiple analyses support an average mutation rate of ~0.3 SNPs per genome per year. However, all analyses revealed a very high degree of variation around this mean, making the confirmation of links proposed by epidemiology, and inference of novel links, difficult. Despite this, in some cases, the phylogenetic context of other strains provided evidence supporting the confident exclusion of previously inferred epidemiological links. CONCLUSIONS: This in-depth analysis of the molecular clock revealed that it is slow and variable over short time scales, which limits its usefulness in transmission studies. However, the superior resolution of whole genome sequencing can provide the phylogenetic context to allow the confident exclusion of possible transmission events previously inferred via traditional DNA fingerprinting techniques and epidemiological cluster investigation. Despite the slow generation of variation even at the whole genome level we conclude that the investigation of tuberculosis transmission will benefit greatly from routine whole genome sequencing.

X Demographics

X Demographics

The data shown below were collected from the profiles of 6 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 230 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 6 3%
Spain 2 <1%
Brazil 1 <1%
Norway 1 <1%
Netherlands 1 <1%
New Zealand 1 <1%
Canada 1 <1%
Denmark 1 <1%
United States 1 <1%
Other 0 0%
Unknown 215 93%

Demographic breakdown

Readers by professional status Count As %
Researcher 61 27%
Student > Ph. D. Student 40 17%
Student > Master 27 12%
Student > Bachelor 15 7%
Professor 11 5%
Other 41 18%
Unknown 35 15%
Readers by discipline Count As %
Agricultural and Biological Sciences 75 33%
Medicine and Dentistry 41 18%
Biochemistry, Genetics and Molecular Biology 33 14%
Immunology and Microbiology 13 6%
Veterinary Science and Veterinary Medicine 9 4%
Other 18 8%
Unknown 41 18%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 30 May 2015.
All research outputs
#6,922,550
of 22,699,621 outputs
Outputs from BMC Infectious Diseases
#2,221
of 7,644 outputs
Outputs of similar age
#58,100
of 192,966 outputs
Outputs of similar age from BMC Infectious Diseases
#39
of 163 outputs
Altmetric has tracked 22,699,621 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 7,644 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.6. This one has gotten more attention than average, scoring higher than 69% 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 192,966 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 163 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.