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Approaches to estimating inbreeding coefficients in clinical isolates of Plasmodium falciparum from genomic sequence data

Overview of attention for article published in Malaria Journal, September 2016
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Title
Approaches to estimating inbreeding coefficients in clinical isolates of Plasmodium falciparum from genomic sequence data
Published in
Malaria Journal, September 2016
DOI 10.1186/s12936-016-1531-z
Pubmed ID
Authors

John D. O’Brien, Lucas Amenga-Etego, Ruiqi Li

Abstract

The advent of whole-genome sequencing has generated increased interest in modelling the structure of strain mixture within clinical infections of Plasmodium falciparum The life cycle of the parasite implies that the mixture of multiple strains within an infected individual is related to the out-crossing rate across populations, making methods for measuring this process in situ central to understanding the genetic epidemiology of the disease. This paper derives a set of new estimators for inferring inbreeding coefficients using whole genome sequence read count data from P. falciparum clinical samples, which provides resources to assess within-sample mixture that connect to extensive literatures in population genetics and conservation ecology. Features of the P. falciparum genome mean that standard methods for inbreeding coefficients and related F-statistics cannot be used directly. After reviewing an initial effort to estimate the inbreeding coefficient within clinical isolates of P. falciparum, several generalizations using both frequentist and Bayesian approaches are provided. A simpler, more intuitive frequentist estimator is shown to have nearly identical properties to the initial estimator both in simulation and in real data sets. The Bayesian approach connects these estimates to the Balding-Nichols model, a mainstay within genetic epidemiology, and a possible framework for more complex modelling. A simulation study shows strong performance for all estimators with as few as ten variants. Application to samples from the PF3K data set indicate significant across-country variation in within-sample mixture. Finally, a comparison with results from a recent mixture model for within-sample strain mixture show that inbreeding coefficients provide a strong proxy for these more complex models. This paper provides a set of methods for estimating inbreeding coefficients within P. falciparum samples from whole-genome sequence data, supported by simulation studies and empirical examples. It includes a substantially simple estimator with similar statistical properties to the estimator in current use. These methods will also be applicable to other species with similar life-cycles. Implementations of the methods described are available in an open-source R package pfmix. Estimates for the PF3K public data release are provide as part of this resource.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 31 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 7 23%
Researcher 6 19%
Student > Ph. D. Student 4 13%
Professor > Associate Professor 3 10%
Student > Master 3 10%
Other 6 19%
Unknown 2 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 7 23%
Biochemistry, Genetics and Molecular Biology 6 19%
Medicine and Dentistry 5 16%
Engineering 3 10%
Computer Science 2 6%
Other 6 19%
Unknown 2 6%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 06 April 2017.
All research outputs
#12,965,815
of 22,888,307 outputs
Outputs from Malaria Journal
#3,180
of 5,579 outputs
Outputs of similar age
#159,966
of 321,166 outputs
Outputs of similar age from Malaria Journal
#51
of 114 outputs
Altmetric has tracked 22,888,307 research outputs across all sources so far. This one is in the 42nd percentile – i.e., 42% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,579 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.8. This one is in the 41st percentile – i.e., 41% of its peers scored the same or lower than it.
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 321,166 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 114 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 54% of its contemporaries.