man Bio::Tree::Statistics (3): Calculate certain statistics for a Tree

SYNOPSIS

use Bio::Tree::Statistics;

DESCRIPTION

This should be where Tree statistics are calculated. It was previously where statistics from a Coalescent simulation.

It now contains several methods for calculating Tree-Trait statistics.

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rather than to the module maintainer directly. Many experienced and reponsive experts will be able look at the problem and quickly address it. Please include a thorough description of the problem with code and data examples if at all possible.

Reporting Bugs

Report bugs to the Bioperl bug tracking system to help us keep track of the bugs and their resolution. Bug reports can be submitted via the web:

  https://github.com/bioperl/bioperl-live/issues

AUTHOR - Jason Stajich

Email jason AT bioperl.org

CONTRIBUTORS

Heikki Lehvaslaiho, heikki at bioperl dot org

APPENDIX

The rest of the documentation details each of the object methods. Internal methods are usually preceded with a _

new

 Title   : new
 Usage   : my $obj = Bio::Tree::Statistics->new();
 Function: Builds a new Bio::Tree::Statistics object 
 Returns : Bio::Tree::Statistics
 Args    :

assess_bootstrap

 Title   : assess_bootstrap
 Usage   : my $tree_with_bs = $stats->assess_bootstrap(\@bs_trees);
 Function: Calculates the bootstrap for internal nodes based on
 Returns : L<Bio::Tree::TreeI>
 Args    : Arrayref of L<Bio::Tree::TreeI>s

cherries

  Example    : cherries($tree, $node);
  Description: Count number of paired leaf nodes
               in a binary tree
  Returns    : integer
  Exceptions : 
  Args       : 1. Bio::Tree::TreeI object
               2. Bio::Tree::NodeI object within the tree, optional

Commonly used statistics assume a binary tree, but this methods returns a value even for trees with polytomies.

Tree-Trait statistics

The following methods produce descriptors of trait distribution among leaf nodes within the trees. They require that a trait has been set for each leaf node. The tag methods of Bio::Tree::Node are used to store them as key/value pairs. In this way, one tree can store more than one trait.

Trees have method add_traits() to set trait values from a file. See the add_trait() method in Bio::Tree::TreeFunctionsI.

fitch

  Example    : fitch($tree, $key, $node);
  Description: Calculates Parsimony Score (PS) and internal trait
               values using the Fitch 1971 parsimony algorithm for
               the subtree a defined by the (internal) node.
               Node defaults to the root.
  Returns    : true on success
  Exceptions : leaf nodes have to have the trait defined
  Args       : 1. Bio::Tree::TreeI object
               2. trait name string
               3. Bio::Tree::NodeI object within the tree, optional

Runs first fitch_up that calculates parsimony scores and then fitch_down that should resolve most of the trait/character state ambiguities.

Fitch, W.M., 1971. Toward defining the course of evolution: minimal change for a specific tree topology. Syst. Zool. 20, 406-416.

You can access calculated parsimony values using:

  $score = $node->->get_tag_values('ps_score');

and the trait value with:

  $traitvalue = $node->->get_tag_values('ps_trait'); # only the first
  @traitvalues = $node->->get_tag_values('ps_trait');

Note that there can be more that one trait value, especially for the root node.

ps

  Example    : ps($tree, $key, $node);
  Description: Calculates Parsimony Score (PS) from Fitch 1971
               parsimony algorithm for the subtree as defined
               by the (internal) node.
               Node defaults to the root.
  Returns    : integer, 1 < PS < n, where n is number of branches
  Exceptions : leaf nodes have to have the trait defined
  Args       : 1. Bio::Tree::TreeI object
               2. trait name string
               3. Bio::Tree::NodeI object within the tree, optional

This is the first half of the Fitch algorithm that is enough for calculating the resolved parsimony values. The trait/chararacter states are commonly left in ambiguous state. To resolve them, run fitch_down.

fitch_up

  Example    : fitch_up($tree, $key, $node);
  Description: Calculates Parsimony Score (PS) from the Fitch 1971
               parsimony algorithm for the subtree as defined
               by the (internal) node.
               Node defaults to the root.
  Returns    : integer, 1< PS < n, where n is number of branches
  Exceptions : leaf nodes have to have the trait defined
  Args       : 1. Bio::Tree::TreeI object
               2. trait name string
               3. Bio::Tree::NodeI object within the tree, optional

This is a more generic name for ps and indicates that it performs the first bottom-up tree traversal that calculates the parsimony score but usually leaves trait/character states ambiguous. If you are interested in internal trait states, running fitch_down should resolve most of the ambiguities.

fitch_down

  Example    : fitch_down($tree, $node);
  Description: Runs the second pass from Fitch 1971
               parsimony algorithm to resolve ambiguous
               trait states left by first pass.
               by the (internal) node.
               Node defaults to the root.
  Returns    : true
  Exceptions : dies unless the trait is defined in all nodes
  Args       : 1. Bio::Tree::TreeI object
               2. Bio::Tree::NodeI object within the tree, optional

Before running this method you should have ran fitch_up (alias to ps ). Note that it is not guaranteed that all states are completely resolved.

persistence

  Example    : persistence($tree, $node);
  Description: Calculates the persistence
               for node in the subtree defined by the (internal)
               node.  Node defaults to the root.
  Returns    : int, number of generations trait value has to remain same
  Exceptions : all the  nodes need to have the trait defined
  Args       : 1. Bio::Tree::TreeI object
               2. Bio::Tree::NodeI object within the tree, optional

Persistence measures the stability that the trait value has in a tree. It expresses the number of generations the trait value remains the same. All the decendants of the root in the same generation have to share the same value.