{"Package":"perfectphyloR","Type":"Package","Title":"Reconstruct Perfect Phylogenies from DNA Sequence Data","Version":"0.2.1","Date":"2021-02-28","Author":"Charith Karunarathna and Jinko Graham","Maintainer":"Charith Karunarathna ","Description":"Reconstructs perfect phylogeny at a user-given focal point and to depict and test association in a genomic region based on the reconstructed partitions. Charith B Karunarathna and Jinko Graham (2019) .","Depends":"R (>= 3.4.0)","License":"GNU General Public License","Imports":"ape, phytools, Rcpp (>= 0.12.16)","LinkingTo":"Rcpp, RcppArmadillo","RoxygenNote":"7.1.1","Suggests":"HHG, dendextend, vcfR, R.rsp","VignetteBuilder":"R.rsp","NeedsCompilation":"yes","Packaged":"2021-03-08 00:26:17 UTC; bhagy","Repository":"CRAN","Date/Publication":"2021-03-08 05:30:02 UTC","repoType":"cran","tarballUrl":"ftp://cran.r-project.org/pub/R/src/contrib/perfectphyloR_0.2.1.tar.gz","readme":"\n\nperfectphyloR\n=============\n\nThe R package perfectphyloR reconstructs perfect phylogenies underlying a sample of DNA sequences, at a focal single-nucleotide variant (SNV). A perfect phylogeny is a rooted binary tree that recursively partitions DNA sequences. Their nested partition structures provide insight into the pattern of ancestry of DNA sequence data. For example, disease sequences may cluster together in a local partition indicating that they arise from a common ancestral haplotypes. Therefore, the availability of an R package that reconstructs perfect phylogenies should be useful to researchers seeking the ancestral structure of their sequence data.\n\nInstallation\n------------\n\nYou can install perfectphyloR from github with:\n\n``` r\n\n# install.packages(\"devtools\")\ndevtools::install_github(\"cbhagya/perfectphyloR\")\n```\n\nExample\n-------\n\nTo reconstruct a perfect phylogeny, you have to first create an object of class `hapMat`. `createHapMat()` allows you to create this new object. To illustrate, we consider a toy example with 4 haplotypes and 4 SNVs.\n\n``` r\nlibrary(perfectphyloR)\n # Haplotype matrix\n haplo_mat <- matrix(c(1,1,1,0,\n 0,0,0,0,\n 1,1,1,1,\n 1,0,0,0), byrow = TRUE, ncol = 4)\n # SNV names\n SNV_names <- c(paste(\"SNV\", 1:4, sep = \"\"))\n # Haplotype names\n hap_names <- c(\"h1\", \"h2\", \"h3\", \"h4\")\n # SNV positions in base pairs\n SNV_posns <- c(1000, 2000, 3000, 4000)\n ex_hapMat <- createHapMat(hapmat = haplo_mat,\n snvNames = SNV_names,\n hapNames = hap_names ,\n posns = SNV_posns)\n ex_hapMat\n#> $hapmat\n#> SNV1 SNV2 SNV3 SNV4\n#> h1 1 1 1 0\n#> h2 0 0 0 0\n#> h3 1 1 1 1\n#> h4 1 0 0 0\n#> \n#> $posns\n#> [1] 1000 2000 3000 4000\n#> \n#> attr(,\"class\")\n#> [1] \"hapMat\"\n```\n\nOnce the `hapMat` object is created, you can reconstruct the perfect phylogeny partition with the function `reconstructPP()`. To illustrate, we show how to reconstruct the partition at the second SNV position of `ex_hapMat`.\n\n``` r\n# Reconstruct the partition at the SNV position 2.\nrdend <- reconstructPP(hapMat = ex_hapMat,\n focalSNV = 2,\n minWindow = 1,\n sep = \"-\")\n```\n\nYou can use `plotDend()` to plot the dendrogram structure of reconstructed partitions at a focal point. The following example shows how you can plot the reconstructed partition `rdend`.\n\n``` r\nplotDend(rdend, direction = \"downwards\")\n```\n\n

","jobInfo":{"package":"perfectphyloR","version":"0.2.1","parsingStatus":"success","parserVersion":1,"parsedAt":"2021-03-08T07:29:47+0000"}}

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