find_graphs_old: Find well fitting admixture graphs

In uqrmaie1/admixtools: Inferring demographic history from genetic data

Find well fitting admixture graphs

Description

This function generates and evaluates admixture graphs in numgen iterations across numrep independent repeats to find well fitting admixturegraphs. It uses the function future_map to parallelize across the independent repeats. The function plan can be called to specify the details of the parallelization. This can be used to parallelize across cores or across nodes on a compute cluster. Setting numadmix to 0 will search for well fitting trees, which is much faster than searching for admixture graphs with many admixture nodes.

Usage

find_graphs_old(
  data,
  pops = NULL,
  outpop = NULL,
  numrep = 1,
  numgraphs = 50,
  numgen = 5,
  numsel = 5,
  numadmix = 0,
  numstart = 1,
  keep = c("all", "best", "last"),
  initgraphs = NULL,
  mutfuns = namedList(spr_leaves, spr_all, swap_leaves, move_admixedge_once,
    flipadmix_random, mutate_n),
  mutprobs = NULL,
  opt_worst_residual = FALSE,
  store_intermediate = NULL,
  parallel = TRUE,
  stop_after = NULL,
  verbose = TRUE,
  ...
)

Arguments

data	Input data in one of three forms: A 3d array of blocked f2 statistics, output of f2_from_precomp or f2_from_geno A directory which contains pre-computed f2-statistics The prefix of genotype files
pops	Populations for which to fit admixture graphs (default all)
outpop	An outgroup population which will split at the root from all other populations in all tested graphs. If one of the populations is know to be an outgroup, designating it as outpop will greatly reduce the search space compared to including it and not designating it as outpop.
numrep	Number of independent repetitions (each repetition can be run in parallel)
numgraphs	Number of graphs in each generation
numgen	Number of generations
numsel	Number of graphs which are selected in each generation. Should be less than numgraphs.
numadmix	Number of admixture events within each graph
numstart	Number of random initializations in each call to qpgraph. Defaults to 1, to speed up the graph optimization.
keep	Which models should be returned. One of all, best, last all (default): Return all evaluated graphs best: Return only the best fitting graph from each repeat and each generation last: Return all graphs from the last generation
initgraphs	Optional graph or list of igraphs to start with. If NULL, optimization will start with random graphs.
mutfuns	Functions used to modify graphs. Defaults to the following: spr_leaves: Subtree prune and regraft leaves. Cuts a leaf node and attaches it to a random other edge in the graph. spr_all: Subtree prune and regraft. Cuts any edge and attaches the new orphan node to a random other edge in the graph, keeping the number of admixture nodes constant. swap_leaves: Swaps two leaf nodes. move_admixedge_once: Moves an admixture edge to a nearby location. flipadmix_random: Flips the direction of an admixture edge (if possible). mutate_n: Apply n of the mutation functions in this list to a graph (defaults to 2). See examples for how to make new mutation functions.
mutprobs	Relative frequencies of each mutation function. NULL (default) means each mutation function is picked with equal probability A numeric vector of length equal to mutfuns defines the relative frequency of each mutation function A matrix of dimensions numgen x length(mutfuns) defines the relative frequency of each mutation function in each generation
opt_worst_residual	Optimize for lowest worst residual instead of best score. FALSE by default, because the likelihood score is generally a better indicator of the quality of the model fit. Optimizing for the lowest worst residual is also slower (because f4-statistics need to be computed).
store_intermediate	Path and prefix of files for intermediate results to .rds. Can be useful if find_graphs_old doesn't finish sucessfully.
parallel	Parallelize over repeats (if numrep > 1) or graphs (if numrep == 1) by replacing map with future_map. Will only be effective if plan has been set.
stop_after	Stop optimization after stop_after seconds (and after finishing the current generation).
verbose	Print progress updates
...	Additional arguments passed to qpgraph

Value

A nested data frame with one model per line

See Also

qpgraph

Examples

## Not run: 
find_graphs_old(example_f2_blocks, numrep = 200, numgraphs = 100,
            numgen = 20, numsel = 5, numadmix = 3)

## End(Not run)
## Not run: 
# Making new mutation functions by modifying or combining existing ones:
newfun1 = function(graph, ...) mutate_n(graph, 3, ...)
newfun2 = function(graph, ...) flipadmix_random(spr_leaves(graph, ...), ...)
find_graphs_old(f2_blocks, mutfuns = namedList(spr_leaves, newfun1, newfun2), mutprobs = c(0.2, 0.3, 0.5))

## End(Not run)

uqrmaie1/admixtools documentation built on Nov. 3, 2024, 12:56 a.m.