# Calculate a dendrogram with bootstrap support using any distance applicable to genind or genclone objects. ```r aboot( x, strata = NULL, tree = "upgma", distance = "nei.dist", sample = 100, cutoff = 0, showtree = TRUE, missing = "mean", mcutoff = 0, quiet = FALSE, root = NULL, ... ) ``` ## Arguments - `x`: a genind-class , genpop-class , genclone-class , adegenet::genlight , snpclone or matrix object. - `strata`: a formula specifying the strata to be used to convert x to a genclone object if x is a genind object. Defaults to `NULL`. See details. - `tree`: a text string or function that can calculate a tree from a distance matrix. Defaults to "upgma". Note that you must load the package with the function for it to work. - `distance`: a character or function defining the distance to be applied to x. Defaults to `nei.dist()`. - `sample`: An integer representing the number of bootstrap replicates Default is 100. - `cutoff`: An integer from 0 to 100 setting the cutoff value to return the bootstrap values on the nodes. Default is 0. - `showtree`: If `TRUE` (Default), a dendrogram will be plotted. If `FALSE`, nothing will be plotted. - `missing`: any method to be used by `missingno()`: "mean" (default), "zero", "loci", "genotype", or "ignore". - `mcutoff`: a value between 0 (default) and 1 defining the percentage of tolerable missing data if the `missing` parameter is set to "loci" or "genotype". This should only be set if the distance metric can handle missing data. - `quiet`: if `FALSE` (default), a progress bar will be printed to screen. - `root`: is the tree rooted? This is a parameter passed off to `ape::boot.phylo()`. If the `tree` parameter returns a rooted tree (like UPGMA), this should be `TRUE`, otherwise (like neighbor-joining), it should be false. When set to `NULL` (default), the tree is considered rooted if `ape::is.ultrametric()` is true. - `...`: any parameters to be passed off to the distance method. ## Returns an object of class `ape::phylo()`. ## Details This function automates the process of bootstrapping genetic data to create a dendrogram with bootstrap support on the nodes. It will randomly sample with replacement the loci of a `gen` (genind/genpop) object or the columns of a numeric matrix, assuming that all loci/columns are independent . The process of randomly sampling `gen` objects with replacement is carried out through the use of an internal class called bootgen . This is necessary due to the fact that columns in the genind matrix are defined as alleles and are thus interrelated. This function will specifically bootstrap loci so that results are biologically relevant. With this function, the user can also define a custom distance to be performed on the genind or genclone object. If you have a data frame-like object where all of the columns are independent or pairs of columns are independent, then it may be simpler to use `ape::boot.phylo()` to calculate your bootstrap support values. ### the strata argument There is an argument called `strata`. This argument is useful for when you want to bootstrap by populations from a `adegenet::genind()` object. When you specify strata, the genind object will be converted to `adegenet::genpop()` with the specified strata. ## Note `prevosti.dist()` and `diss.dist()` are exactly the same, but `diss.dist()` scales better for large numbers of individuals (n > 125) at the cost of required memory. ### missing data Missing data is not allowed by many of the distances. Thus, one of the first steps of this function is to treat missing data by setting it to the average allele frequency in the data set. If you are using a distance that can handle missing data (Prevosti's distance), you can set `missing = "ignore"` to allow the distance function to handle any missing data. See `missingno()` for details on missing data. ### Bruvo's Distance While calculation of Bruvo's distance is possible with this function, it is optimized in the function `bruvo.boot()`. ## Examples ```r data(nancycats) nan9 <- popsub(nancycats, 9) set.seed(9999) # Generate a tree using nei's distance neinan <- aboot(nan9, dist = nei.dist) set.seed(9999) # Generate a tree using custom distance bindist <- function(x) dist(tab(x), method = "binary") binnan <- aboot(nan9, dist = bindist) ## Not run: # Distances from other packages. # # Sometimes, distance functions from other packages will have the constraint # that the incoming data MUST be genind. Internally, aboot uses the # bootgen class ( class?bootgen ) to shuffle loci, and will throw an error # The function bootgen2genind helps fix that. Here's an example of a function # that expects a genind class from above bindist <- function(x){ stopifnot(is.genind(x)) dist(tab(x), method = "binary") } # # Fails: # aboot(nan9, dist = bindist) ## Error: is.genind(x) is not TRUE # # Add bootgen2genind to get it working! # Works: aboot(nan9, dist = function(x) bootgen2genind(x) %>% bindist) # AFLP data data(Aeut) # Nei's distance anei <- aboot(Aeut, dist = nei.dist, sample = 1000, cutoff = 50) # Rogers' distance arog <- aboot(Aeut, dist = rogers.dist, sample = 1000, cutoff = 50) # This can also be run on genpop objects strata(Aeut) <- other(Aeut)$population_hierarchy[-1] Aeut.gc <- as.genclone(Aeut) setPop(Aeut.gc) <- ~Pop/Subpop Aeut.pop <- genind2genpop(Aeut.gc) set.seed(5000) aboot(Aeut.pop, sample = 1000) # compare to Grunwald et al. 2006 # You can also use the strata argument to convert to genpop inside the function. set.seed(5000) aboot(Aeut.gc, strata = ~Pop/Subpop, sample = 1000) # And genlight objects # From glSim: ## 1,000 non structured SNPs, 100 structured SNPs x <- glSim(100, 1e3, n.snp.struc=100, ploid=2) aboot(x, distance = bitwise.dist) # Utilizing other tree methods library("ape") aboot(Aeut.pop, tree = fastme.bal, sample = 1000) # Utilizing options in other tree methods myFastME <- function(x) fastme.bal(x, nni = TRUE, spr = FALSE, tbr = TRUE) aboot(Aeut.pop, tree = myFastME, sample = 1000) ## End(Not run) ``` ## References Kamvar ZN, Brooks JC and Grünwald NJ (2015) Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality. Frontiers in Genetics 6:208. tools:::Rd_expr_doi("10.3389/fgene.2015.00208") ## See Also `nei.dist()` `edwards.dist()` `rogers.dist()` `reynolds.dist()` `prevosti.dist()` `diss.dist()` `bruvo.boot()` `ape::boot.phylo()` `adegenet::dist.genpop()` `dist()` `bootgen2genind()` bootgen

aboot function