ancestral_state_reconstruction.py – Runs ancestral state reconstruction given a tree and trait table

Description:

Provides a common interface for running various ancenstral state reconstruction methods (e.g. ACE, BayesTraits, etc.).

Usage: ancestral_state_reconstruction.py [options]

Input Arguments:

Note

[REQUIRED]

-t, --input_tree_fp

The tree to use for ASR

-i, --input_trait_table_fp

The trait table to use for ASR

[OPTIONAL]

-m, --asr_method

Method for ancestral state reconstruction. Valid choices are: ace_ml, ace_reml, ace_pic, wagner [default: ace_pic]

-o, --output_fp

Output trait table [default:asr_counts.tab]

-c, --output_ci_fp

Output table containing 95% confidence intervals, loglik, and brownian motion parameters for each asr prediction [default:asr_ci.tab]

-p, --parallel

Allow parallelization of asr

-j, --parallel_method

Method for parallelizaation. Valid choices are: sge, torque, multithreaded [default: sge]

-n, --num_jobs

Number of jobs to be submitted (if –parallel). [default: 100]

-d, --debug

To aid with debugging; get the command that the app controller is going to run

Output:

A table containing trait information for internal nodes of the tree.

Example 1:

Provide a tree file and trait table file:

ancestral_state_reconstruction.py -i trait_table.tab -t pruned_tree.newick -o asr_counts.tab -c asr_ci.tab