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Title:   Author  item
                                            KAMVAR, ZHIAN - Oregon State Universityitem
                                            BROOKS, JONAH - Oregon State Universityitem
                                            Grunwald, Niklaus

                                                         - *Nik*
  Submitted to: Frontiers in Genetics
                                    Publication Type: Peer Reviewed Journal
                                    Publication Acceptance Date: 5/29/2015
                                    Publication  Date: 6/10/2015
                                    Citation: Kamvar, Z.N., Brooks, J.C., Grunwald, N.J. 2015. Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality. Frontiers in Genetics. 6:208. doi: 10.3389/fgene.2015.00208.Interpretive Summary: To gain a detailed understanding of how plant microbes evolve and adapt to agricultural environments, knowledge of the population dynamics 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. In this paper we provide several novel functions with a focus on large, genome-wide, genetic data useful for characterizing populations of microbes, whether clonal or not.
                                Technical 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 functionmlg.filter to define clone boundaries allowing for inspection and definition of what is a clonal lineage, a sliding-window analysis of the index of association, modular bootstrapping of any genetic distance, and analyses across any level of hierarchies.


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