hierBAPS: hierBAPS

In gtonkinhill/rhierbaps: Clustering Genetic Sequence Data Using the HierBAPS Algorithm

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
)

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.

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.

Author(s)

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)


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)})

gtonkinhill/rhierbaps documentation built on May 3, 2021, 9:04 p.m.