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Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality.

Kamvar ZN, Brooks JC, Grünwald NJ - Front Genet (2015)

Bottom Line: We previously contributed the R package poppr specifically addressing issues with analysis of clonal populations.In this paper we provide several significant extensions to poppr with a focus on large, genome-wide SNP data.Specifically, we provide several new functionalities including the new function mlg.filter to define clone boundaries allowing for inspection and definition of what is a clonal lineage, minimum spanning networks with reticulation, a sliding-window analysis of the index of association, modular bootstrapping of any genetic distance, and analyses across any level of hierarchies.

View Article: PubMed Central - PubMed

Affiliation: Botany and Plant Pathology, Oregon State University Corvallis, OR, USA.

ABSTRACT
To gain a detailed understanding of how plant microbes evolve and adapt to hosts, pesticides, and other factors, knowledge of the population dynamics and evolutionary history of populations is crucial. Plant pathogen populations are often clonal or partially clonal which requires different analytical tools. With the advent of high throughput sequencing technologies, obtaining genome-wide population genetic data has become easier than ever before. We previously contributed the R package poppr specifically addressing issues with analysis of clonal populations. In this paper we provide several significant extensions to poppr with a focus on large, genome-wide SNP data. Specifically, we provide several new functionalities including the new function mlg.filter to define clone boundaries allowing for inspection and definition of what is a clonal lineage, minimum spanning networks with reticulation, a sliding-window analysis of the index of association, modular bootstrapping of any genetic distance, and analyses across any level of hierarchies.

No MeSH data available.


Genotype accumulation curve for 694 isolates of the peach brown rot pathogen,Monilinia fructicolagenotyped over 13 loci from Everhart and Scherm (2015). The horizontal axis represents the number of loci randomly sampled without replacement up to (n − 1) loci, the vertical axis shows the number of multilocus genotypes observed, up to 262, the number of unique multilocus genotypes in the data set. The red dashed line represents 90% of the total observed multilocus genotypes. A trendline (blue) has been added using the ggplot2 function stat_smooth.
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Figure 5: Genotype accumulation curve for 694 isolates of the peach brown rot pathogen,Monilinia fructicolagenotyped over 13 loci from Everhart and Scherm (2015). The horizontal axis represents the number of loci randomly sampled without replacement up to (n − 1) loci, the vertical axis shows the number of multilocus genotypes observed, up to 262, the number of unique multilocus genotypes in the data set. The red dashed line represents 90% of the total observed multilocus genotypes. A trendline (blue) has been added using the ggplot2 function stat_smooth.

Mentions: The following code example demonstrates the genotype accumulation curve for data from Everhart and Scherm (2015) showing that these data reach a small plateau and have a greatly decreased variance with 12 markers, indicating that there are enough markers such that adding more markers to the analysis will not create very many new genotypes (Figure 5).


Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality.

Kamvar ZN, Brooks JC, Grünwald NJ - Front Genet (2015)

Genotype accumulation curve for 694 isolates of the peach brown rot pathogen,Monilinia fructicolagenotyped over 13 loci from Everhart and Scherm (2015). The horizontal axis represents the number of loci randomly sampled without replacement up to (n − 1) loci, the vertical axis shows the number of multilocus genotypes observed, up to 262, the number of unique multilocus genotypes in the data set. The red dashed line represents 90% of the total observed multilocus genotypes. A trendline (blue) has been added using the ggplot2 function stat_smooth.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4462096&req=5

Figure 5: Genotype accumulation curve for 694 isolates of the peach brown rot pathogen,Monilinia fructicolagenotyped over 13 loci from Everhart and Scherm (2015). The horizontal axis represents the number of loci randomly sampled without replacement up to (n − 1) loci, the vertical axis shows the number of multilocus genotypes observed, up to 262, the number of unique multilocus genotypes in the data set. The red dashed line represents 90% of the total observed multilocus genotypes. A trendline (blue) has been added using the ggplot2 function stat_smooth.
Mentions: The following code example demonstrates the genotype accumulation curve for data from Everhart and Scherm (2015) showing that these data reach a small plateau and have a greatly decreased variance with 12 markers, indicating that there are enough markers such that adding more markers to the analysis will not create very many new genotypes (Figure 5).

Bottom Line: We previously contributed the R package poppr specifically addressing issues with analysis of clonal populations.In this paper we provide several significant extensions to poppr with a focus on large, genome-wide SNP data.Specifically, we provide several new functionalities including the new function mlg.filter to define clone boundaries allowing for inspection and definition of what is a clonal lineage, minimum spanning networks with reticulation, a sliding-window analysis of the index of association, modular bootstrapping of any genetic distance, and analyses across any level of hierarchies.

View Article: PubMed Central - PubMed

Affiliation: Botany and Plant Pathology, Oregon State University Corvallis, OR, USA.

ABSTRACT
To gain a detailed understanding of how plant microbes evolve and adapt to hosts, pesticides, and other factors, knowledge of the population dynamics and evolutionary history of populations is crucial. Plant pathogen populations are often clonal or partially clonal which requires different analytical tools. With the advent of high throughput sequencing technologies, obtaining genome-wide population genetic data has become easier than ever before. We previously contributed the R package poppr specifically addressing issues with analysis of clonal populations. In this paper we provide several significant extensions to poppr with a focus on large, genome-wide SNP data. Specifically, we provide several new functionalities including the new function mlg.filter to define clone boundaries allowing for inspection and definition of what is a clonal lineage, minimum spanning networks with reticulation, a sliding-window analysis of the index of association, modular bootstrapping of any genetic distance, and analyses across any level of hierarchies.

No MeSH data available.