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bioRxiv · 10.1101/2020.09.05.284109

ClinePlotR: Visualizing genomic clines and detecting outliers in R

Martin, B. T.·Chafin, T. K.·Douglas, M. R.·Douglas, M. E.
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Abstract

Patterns of multi-locus differentiation (i.e., genomic clines) often extend broadly across hybrid zones and their quantification can help diagnose how species boundaries are shaped by adaptive processes, both intrinsic and extrinsic. In this sense, the transitioning of loci across admixed individuals can be contrasted as a function of the genome-wide trend, in turn allowing an expansion of clinal theory across a much wider array of biodiversity. However, computational tools that serve to interpret and consequently visualize genomic clines are limited. Here, we introduce the CO_SCPLOWLINEC_SCPLOWPO_SCPLOWLOTC_SCPLOWR R-package for visualizing genomic clines and detecting outlier loci using output generated by two popular software packages, O_SCPLOWBGCC_SCPLOW and IO_SCPLOWNTROGRESSC_SCPLOW. CO_SCPLOWLINEC_SCPLOWPO_SCPLOWLOTC_SCPLOWR bundles both input generation (i.e, filtering datasets and creating specialized file formats) and output processing (e.g., MCMC thinning and burn-in) with functions that directly facilitate interpretation and hypothesis testing. Tools are also provided for post-hoc analyses that interface with external packages such as ENMO_SCPLOWEVALC_SCPLOW and RIO_SCPLOWDEOGRAMC_SCPLOW. Our package increases the reproducibility and accessibility of genomic cline methods, thus allowing an expanded user base and promoting these methods as mechanisms to address diverse evolutionary questions in both model and non-model organisms.

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Martin, B. T., Chafin, T. K., Douglas, M. R., Douglas, M. E.. 2020-09-08. ClinePlotR: Visualizing genomic clines and detecting outliers in R. https://doi.org/10.1101/2020.09.05.284109

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