rhierbaps (version 1.1.4)

hierBAPS: hierBAPS

Description

Runs the hierBAPS algorithm of Cheng et al. 2013

Usage

hierBAPS(
  snp.matrix,
  max.depth = 2,
  n.pops = floor(nrow(snp.matrix)/5),
  quiet = FALSE,
  n.extra.rounds = 0,
  assignment.probs = FALSE,
  n.cores = 1
)

Value

A list containing a dataframe indicating an assignment of each sequence to hierarchical clusters as well as the log marginal likelihoods for each level.

Arguments

snp.matrix

Character matrix of aligned sequences produced by load_fasta.

max.depth

Maximum depth of hierarchical search (default = 2).

n.pops

Maximum number of populations in the data (default = number of isolates/5)

quiet

Whether to suppress progress information (default=FALSE).

n.extra.rounds

The number of additional rounds to perform after the default hierBAPS settings (default=0). If set to Inf it will run until a local optimum is reached (this might take a long time).

assignment.probs

whether or not to calculate the assignment probabilities to each cluster (default=FALSE)

n.cores

The number of cores to use.

Author

Gerry Tonkin-Hill

References

Cheng, Lu, Thomas R. Connor, Jukka Sirén, David M. Aanensen, and Jukka Corander. 2013. “Hierarchical and Spatially Explicit Clustering of DNA Sequences with BAPS Software.” Molecular Biology and Evolution 30 (5): 1224–28.

Examples

snp.matrix <- load_fasta(system.file("extdata", "small_seqs.fa", package = "rhierbaps"))
hb <- hierBAPS(snp.matrix, max.depth=2, n.pops=20, quiet=FALSE)

# \donttest{
snp.matrix <- load_fasta(system.file("extdata", "seqs.fa", package = "rhierbaps"))
system.time({hb <- hierBAPS(snp.matrix, max.depth=2, n.pops=20, quiet=FALSE)})
# }