{"Package":"wingen","Title":"Continuous Mapping of Genetic Diversity","Version":"2.1.1","Authors@R":"c(\nperson(\"Anusha\", \"Bishop\", , email = \"anusha.bishop@berkeley.edu\", role = c(\"aut\", \"cre\"),\ncomment = c(ORCID = \"0000-0003-1731-8683\")),\nperson(\"Anne\", \"Chambers\", , email = \"eachambers@berkeley.edu\", role =\"aut\",\ncomment = c(ORCID = \"0000-0002-7369-0108\")),\nperson(\"Ian\", \"Wang\", , email = \"ianwang@berkeley.edu\", role = \"aut\",\ncomment = c(ORCID = \"0000-0003-2554-9414\"))\n)","Description":"Generate continuous maps of genetic diversity using moving windows with options for rarefaction, interpolation, and masking as described in Bishop et al. (2023) .","License":"MIT + file LICENSE","Encoding":"UTF-8","LazyData":"true","RoxygenNote":"7.3.1","Imports":"automap, crayon, dplyr, furrr, gdistance, graphics, grDevices,\nggplot2, hierfstat, magrittr, pegas, purrr, raster, rlang, sf,\nterra, tidyr, tidyselect, utils, vcfR, viridis","Suggests":"adegenet, covr, devtools, future, knitr, MASS, rmarkdown,\nstringr, SpatialKDE, testthat (>= 3.0.0)","VignetteBuilder":"knitr","Config/testthat/edition":"3","Depends":"R (>= 3.5.0)","NeedsCompilation":"no","Packaged":"2024-02-25 18:16:05 UTC; wanglab","Author":"Anusha Bishop [aut, cre] (),\nAnne Chambers [aut] (),\nIan Wang [aut] ()","Maintainer":"Anusha Bishop ","Repository":"CRAN","Date/Publication":"2024-02-27 16:40:03 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/wingen_2.1.1.tar.gz","jsonAuthors":[{"name":"Anusha Bishop","email":"anusha.bishop@berkeley.edu","maintainer":true},{"name":"Anne Chambers","email":"eachambers@berkeley.edu","maintainer":false},{"name":"Ian Wang","email":"ianwang@berkeley.edu","maintainer":false}],"readme":"\n\n\n# wingen

\n\n\n\n[![codecov](https://codecov.io/gh/AnushaPB/wingen/graph/badge.svg?token=P4Z35HFR4Y)](https://app.codecov.io/gh/AnushaPB/wingen)\n[![R-CMD-check](https://github.com/AnushaPB/wingen/actions/workflows/R-CMD-check.yaml/badge.svg)](https://github.com/AnushaPB/wingen/actions/workflows/R-CMD-check.yaml)\n [![Zenodo\nDOI](https://zenodo.org/badge/499617621.svg)](https://zenodo.org/badge/latestdoi/499617621)\n\n\nGenerate continuous maps of genetic diversity using moving windows with\noptions for rarefaction, interpolation, and masking.\n\n![](man/figures/README-gif.gif)\n\n## Citation\n\nPlease cite the original Bishop et al. (2023) paper if you use this\npackage:\n\n**Bishop, A. P., Chambers, E. A., & Wang, I. J. (2023). Generating\ncontinuous maps of genetic diversity using moving windows. ***Methods in\nEcology and Evolution***, 14, 1175–1181.\n**\n\nCheckout our [Methods blog\npost](https://methodsblog.com/2023/05/03/wingen-mapping-genetic-diversity-using-moving-windows/)\nabout wingen for a quick overview of the package and its uses.\n\n## Installation\n\nInstall wingen from [GitHub](https://github.com/) with:\n\n``` r\n# install.packages(\"devtools\")\ndevtools::install_github(\"AnushaPB/wingen\", build_vignettes = TRUE)\n```\n\n## Example\n\nThe following example demonstrates the basic functionality of wingen\nusing a **small subset (100 variant loci x 100 samples) of the simulated\ndata from [Bishop et\nal. (2023)](http://doi.org/10.1111/2041-210X.14090)**.\n\n``` r\nlibrary(wingen)\n\n# Load ggplot for plotting\nlibrary(ggplot2)\n\n# Load example data\nload_middle_earth_ex()\n```\n\nThe core function of this package is `window_gd()`, which takes as\ninputs a vcfR object (or a path to a .vcf file), sample coordinates (as\na data.frame, matrix, or sf object), and a raster layer (as a SpatRaster\nor RasterLayer) which the moving window will slide across. Users can\ncontrol the genetic diversity statistic that is calculated (`stat`), the\nwindow dimensions (`wdim`), the aggregation factor to use on the raster\n(`fact`), whether to perform rarefaction (`rarify`), and other aspects\nof the moving window calculations. Additional arguments for this\nfunction are described in the vignette and function documentation.\n\n``` r\n# Run moving window calculations of pi with rarefaction\nwgd <- window_gd(lotr_vcf,\n lotr_coords,\n lotr_lyr,\n stat = \"pi\",\n wdim = 7,\n fact = 3,\n rarify = TRUE\n)\n\n# Use ggplot_gd() to plot the genetic diversity layer and ggplot_count() to plot the sample counts layer\nggplot_gd(wgd) +\n ggtitle(\"Moving window pi\")\n```\n\n![](README_files/figure-gfm/window_gd-1.png)\n\n``` r\nggplot_count(wgd) +\n ggtitle(\"Moving window sample counts\")\n```\n\n![](README_files/figure-gfm/unnamed-chunk-2-1.png)\n\nNext, the output from `window_gd()` can be interpolated using kriging\nwith the `krig_gd()` function.\n\n``` r\n# Krige genetic diversity (disaggregate grid to project across a smoother final surface)\nkgd <- krig_gd(wgd, lotr_lyr, index = 1, disagg_grd = 2)\n```\n\nFinally, the output from `krig_gd()` (or `window_gd()`) can be masked to\nexclude areas that fall outside of the study area or that were\nundersampled.\n\n``` r\n# Mask results that fall outside of the \"range\"\nmgd <- mask_gd(kgd, lotr_range)\n```\n\n``` r\n# Plot results\nggplot_gd(kgd) +\n ggtitle(\"Kriged pi\")\n```\n\n![](README_files/figure-gfm/result-1.png)\n\n``` r\nggplot_gd(mgd) +\n ggtitle(\"Masked pi\")\n```\n\n![](README_files/figure-gfm/result-2.png)\n\nFor an extended walk through, see the package vignette:\n\n``` r\nvignette(\"wingen-vignette\")\n```\n\nA pdf of the vignette can also be found\n[here](https://github.com/AnushaPB/wingen/blob/main/vignettes/wingen-vignette.pdf)\n\nExample analyses from [Bishop et\nal. (2023)](http://doi.org/10.1111/2041-210X.14090) can be found in the\n[paperex](https://github.com/AnushaPB/wingen/tree/main/paperex)\ndirectory.","jobInfo":{"package":"wingen","version":"2.1.1","parsingStatus":"success","parserVersion":2,"parsedAt":"2024-02-27T18:29:57+0000"}}

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