augur.traits

Infer ancestral traits based on a tree.

augur.traits.mugration_inference(tree=None, seq_meta=None, field='country', confidence=True, missing='?', sampling_bias_correction=None, weights=None)

Infer likely ancestral states of a discrete character assuming a time reversible model.

Parameters:

  • tree (str) – name of tree file

  • seq_meta (pandas.DataFrame) – meta data associated with sequences

  • field (str, optional) – meta data field to use

  • confidence (bool, optional) – calculate confidence values for inferences

  • missing (str, optional) – character that is to be interpreted as missing data, default=’?’

  • sampling_bias_correction (None, optional) – factor by which the transition rate is scaled up to counter sampling bias

  • weights (None, optional) – vector of equilibrium frequencies that one expects the far ancestor to be sampled from

Returns:

  • T (Phylo.Tree) – Biophyton tree

  • gtr (treetime.GTR) – GTR model

  • alphabet (dict) – mapping of character states to

augur.traits.register_parser(parent_subparsers)

Add subcommand specific arguments

Parameters:

parser (argparse) – subcommand argument parser

augur.traits.run(args)

run mugration inference

Parameters:

args (namespace) – command line arguments are parsed by argparse