ADViewpy 0.7a0

ADViewpy is Python Library to visually compare phylogenetic trees

ADViewpy

Introduction

ADViewpy pip package is a Python port of ADView system, originally developed by Professor Zipeng Liu. ADViewpy aims to provide visual comparison of phylogenetic trees, usually between one reference tree and a collection of hundreds of trees.

• ADView System by Professor Zipeng Liu: GitHub | ADView Website

The alpha version of this tool has been uploaded to PyPI.

Contributors

Wengshan NG

Features

• Visual comparison of phylogenetic trees
• Easy integration with existing Python workflows

Installation

Installation Steps

1. Install ADViewpy package from PyPI:

   pip install adviewpy
   

2. Import the ADViewpy package and initialize it in your Python script:

   import ADViewpy
   
   # Initialize the ADViewpy tool
   ADViewpy.init()
   

Usage

1.init(treefile)

Initializes ADViewpy and creates the reference tree.

Parameter:

• treefile (str): Path to the reference tree file in Newick format.

Return:

• ADViewpy instance

2.add_tree_collection(treefile,namefile)

Add tree collection to ADViewpy

Parameters:

• treefile (str): Path to the tree collection file (each line contains a tree in newick format).
• nanefile (str): Path to the tree collection's name file, a name of tree each line corresponding to tree collection file.

3.set_outgroup(outgroup_taxon[])

Specify outgroup of phylogenetic tree, ADViewpy will re-root the trees according to outgroup provdied.

Parameter:

• outgroup_taxon[] (list): List of taxa names in outgroup

4.reference_tree(exact_match_range[],support_value_range[])

Visualization of reference tree, user can find branch with respect to attribute range.

Parameters:

• exact_match_range[] (list): A list to represent node exact match percentage range, for example [80, 100], which represents to find nodes with exact match percentage between 80% and 100%.

• support_value_range (list): A list to represent node support value range, for example [50, 80], which represents to find nodes with support value between 50 and 80.

5.AD(view,scale,context_level,max_ad,ad_interval,tree_id,tree_name,sort,escape_taxa_as_context_block,show_block_proportional,subtree_independent,show_tree_name,filter,differentiate_inexact_match)

Visualization of individual and cluster aggregated dendrograms, to show topological relationships between the selected focal subtree.

Common parameters:

• view (str): AD Individual to show individual aggregated dendrograms, AD Cluster to show cluster aggregated dendrograms.
• scale (foat): Set the scale of aggregated dendrograms, default scale is 0.1.

Parameters in individual view:

• context_level (int): Control how many context blocks to show.
• max_ad (int): Set the maximum number of aggregated dendrograms to display.
• ad_interval(list): List to represent tree id range, for example [1, 20], which represents to show aggregated dendrograms with tree id between 1 and 20.
• tree_id (list): Each integer in list represents a tree ID. Only trees matching these IDs will be displayed.
• tree_name(list): Each str in list represents a tree name. Only trees matching these names will be displayed.
• sort(str): Specify how to sort the displayed aggregated dendrograms, can choose from id, name, and rf distance.
• escape_taxa_as_context_block(Boolean): Determine whether escape taxa should be considered as a context block.
• show_block_proportional (Boolean): Determine whether to use color coverage to indicate the percentage of highlighted taxa within subtree
• subtree_independent (Boolean): Determine whether to merge overlapping subtrees into a single block.
• show_tree_name (Boolean): Determine whether to show tree id and tree name on top of each aggregated dendrogram.
• filter (str): Specify whether the conditions are inclusive or exclusive for the following parameters: ad_interval, tree_id,tree_name.

Parameter in cluster view:

• differentiate_inexact_match (Boolean): Choose whether to further distinguish exact and inexact matches in cluster

6.pairwise_comparison(compare_tree)

Pairwise compare two trees in detail. Allow to pairwise compare one tree in the collection with the reference tree or compare two trees in tree collection.

To compare a tree in the collection with the reference tree, user can choose a tree from AD()'s output view with mouse click.

Parameter:

compare_tree (int/str/list): Specify the trees for pairwise comparison. A tree can be specified using IDs or names. Providing an ID or name selects a single tree from the tree collection to compare with a reference tree. If a list is provided containing two trees, it indicates comparison between trees within the collection.

7.tree_distribution()

Showing distributions of trees in terms of their agreement and conflicts of leaf memberships for user-selected subtrees.

8.tree_distance()

Display the distances between each trees using a scatter plot.

Return:

• Plotly scatter showing distances between trees computed by the t-SNE dimensionality reduction technique.

9.export_image(view,filename,*args)

Exports generated view as an image

Parameter:

view (str): Selects which view to export. Choices include Reference Tree,AD Individual,AD Cluster,Tree Distribution,Tree Distance,Pairwise Comparison.