GitLocker: The Coding Marketplace

Description:

ontoloviz 1.7.5

OntoloViz is a user-friendly interface that enables the creation of interactive sunburst plots for
biomedical ontologies. It allows you to conveniently visualize your data for reports or share the
generated plots with collaborators. Check out the examples section
to download interactive .html examples and to gain a better understanding of the package's capabilities.

Quickstart
The GUI can be run by downloading the latest release
or by installing the package via PyPi (OS independent, requires Python 3.8+):
pip install ontoloviz

After the installation you can run the GUI from the command line with the following command:
ontoloviz

Usage
The application allows importing .tsv and .xlsx files, but the use of .tsv and tab as a
separator is recommended. The GUI can create two types of sunburst diagrams to represent either phenotype or drug
ontologies, which is determined by the structure of the loaded files. Any numbers entered in the input file will be converted
to integers and decimal points will be rounded.
GUI Options

Load File: load an .tsv or .xlsx file containing ontology data based below defined file formats
Load from Web: load an .obo ontology from a pre-defined list, or define a URL to any ontology
General options

Set Color Scale: define a custom color scale for the sunburst color scaling when color propagation is active
Set Border: configures the border properties drawn around sunburst wedges
Drop empty nodes (phenotype sunburst only): drops nodes who have no further children and 0 counts
Wedge Width (drug sunburst only): switch from full outer circle (total) to count-based wedge widths (remainder)
Display Labels: controls display of labels inside sunburst wedges, available options:

all
propagation
drugs (drug sunburst only)
none

Legend: displays a weighted color bar (disabled for summary plots with specific color propagation enabled)

Propagation options

Enable: enables count- and color propagation from child to parent nodes
Color: controls color propagation by the options:

off: color scale is based on 'Color' column from imported file
specific: color scale is based on the maximum values of the corresponding subtree
global: color scale is based on the maximum values of the entire tree ontology
phenotype (phenotype sunburst only): Only the most outer phenotype in a branch is colored

Counts: controls count propagation by the options:

off: no counts are propagated, counts equal imported values
level: counts are propagated up to defined level, values above threshold remain unchanged
all: counts are propagated up to central node, imported values are corrected and overwritten

Level: controls color- and count-propagation from outer to inner levels up to defined level

affects color propagation when Color is set to specific or global
affects count propagation when Counts is set to level
drug sunburst: 1 corresponds to the central node, 5 to the outermost node (=drug)
phenotype sunburst: 0 corresponds to the central node, 13 to the outermost node

Summary options

Enable: displays all available subtrees in a single view
(resource intensive, set Labels to none for faster loading)
Columns: defines the amount of columns when summary plot is enabled

Save and Plot options

Save: when enabled, an interactive .html file containing the plot as well as a .tsv file containing the ontology data based on the current settings is generated for later use
Plot: Process and generate plot, opens in a Browser window

MeSH Ontology
This separator-based ontology follows the principles of the MeSH tree.

A Tree ID is defined by a combination of three numbers or letters, for example C01.
Levels are separated by a dot ., for example C01.001.
Ontologies up to thirteen hierarchical levels are supported.
A single phenotype end-node can be assigned to multiple parent-nodes by specifying the parents tree ids as
a pipe separated string in the column Tree ID, for example C01.001.001|C02.001.001.
If a child element is defined without a valid parent node existing, the GUI generates all parent elements with the default color and value 0. For example, the node 123.001 is automatically generated if only the child node 123.001.001 was defined. This works only if at least the most central node 123 was defined manually.
Counts entered in the file will be converted to integers. If a node should be displayed without counts, use 0.
The loaded file must contain 7 columns and follow the below structure to be correctly recognized:

Column Index
Header Text
Description

0
MeSH ID
Required primary identifier of a node in format C01.001

1
Tree ID
Required | pipe delimited list of Tree IDs of a node (allows 1:N mappings)

2
Name
Optional label to be displayed inside the sunburst wedges

3
Description
Optional description displayed in the sunburst wedge tooltip

4
Comment
Optional comment displayed in the sunburst wedge tooltip

5
Counts [Name]
Required count for wedge weights, Name will be used as figure title

6
Color
Optional color for the sunburst wedges, must be hex-string in format #FFFFFF

ATC Ontology
This kind of sunbursts have a fixed hierarchy of 5 levels and are based on the ATC tree.

ATC codes are divided into five levels, which must follow the following naming conventions:

1st level: letter
2nd level: two numbers
3rd level: letter
4th level: letter
5th level: two numbers

Example ATC code: A10BA02
The hierarchy does only allow 1:1 child-parent relationships, contrary to the other ontologies.
For example, if the drug deltatonin should be assigned to the
parent nodes A01AA and B01BB, it must be defined twice with the ids A01AA01 and B01BB01.
The loaded file must contain 6 columns and follow the below structure to be correctly
recognized as a ATC ontology:

Column Index
Header Text
Description

0
ATC code
Required primary identifier of a node in format A10BA02

1
Level
Optional level as number, not used for building tree

2
Label
Optional label to be displayed inside the sunburst wedges

3
Comment
Optional comment displayed in the sunburst wedge tooltip

4
Counts [Name]
Required count for wedge weights, Name will be used as figure title

5
Color
Optional color for the sunburst wedges, must be hex-string in format #FFFFFF

Custom Separator-based Ontologies
OntoloViz supports loading of custom ontologies - if no known format is detected, a prompt will ask
whether the loaded file is a separator-based ontology or if it does contain identifiers with child-
and parent-ids. For separator-based ontologies, the following separators are supported: . (dot), , (colon), _ (underscore), / (slash).
To generate such an ontology, the following 5-column layout is required:

Column Index
Header Text
Description

0
ID
Required node identifier of a node in format A.1 - multiple IDs can be separated with | (pipe)

1
Label
Optional label to be displayed inside the sunburst wedges

2
Comment
Optional comment displayed in the sunburst wedge tooltip

3
Count
Optional count for wedge weights

4
Color
Optional color for the sunburst wedges, must be hex-string in format #FFFFFF

Custom Parent-based Ontologies
For loading any ontology with arbitrary IDs that do not follow a structured schema, the definition of a child-parent relationship using a 6-column layout is required:

Column Index
Header Text
Description

0
ID
Required node identifier in any format - multiple IDs can be separated with | (pipe)

1
Parent
Required parent identifier in any format - if parent ID does not exist, node will be removed

2
Label
Optional label to be displayed inside the sunburst wedges

3
Comment
Optional comment displayed in the sunburst wedge tooltip

4
Count
Optional count for wedge weights

5
Color
Optional color for the sunburst wedges, must be hex-string in format #FFFFFF

Templates and Examples

Filename
Description

atc_example_covid_drugs_experimental.tsv
ATC-based example with data from the DrugBank indicating experimental drugs related to COVID-19.

atc_example_covid_drugs_trial_summary.tsv
ATC-based example with data from publicly available clinical trial data indicating drugs tested in clinical studies, one count represents usage in one study.

atc_template.tsv
ATC-based empty template of the ATC tree based on the manually curated chemical database of bioactive molecules ChEMBL v29.

custom_template_parent_based.tsv
Template for creating your own ontology based on any child and parent terms.

custom_template_separator_based.tsv
Template to create your own ontology based on a separator-based tree structure - for this template the underscore character _ has been used.

mesh_example_pubmed_mapped.tsv
MeSH-based example with data from the publicly available PubMed database of publications (title + abstract), where disease-related MeSH terms were extracted and mapped to the MeSH-tree.

mesh_template.tsv
MeSH-based empty template of the MeSH tree C and F03. Terms are unique and mapped to all related parent nodes.

atc_example.html
ATC-based sample plot generated with the provided covid_drugs_trial_summary.tsv file.

mesh_example.html
MeSH-based sample plot generated with the provided covid_drugs_trial_summary.tsv file.

Screenshots and Demos

Demo 1: Minimal example for creating a phenotype based ontology

Demo 2: Showcase of some of the features available in OntoloViz (used template: test_tree.zip)

Screenshot 1: Drug sunburst plot with enabled labels, counts propagated up to level 3

Screenshot 2: Summary phenotype sunburst plot with tooltip, counts propagated up to the central node, color coded

Screenshot 3 & 4: Left: define automatic color scales based on defined counts with thresholds and hex color codes, Right: define border properties (width, opacity, colors) or disable them entirely

Special Thanks to

Paul Perco, who had the initial idea for this package and provided support throughout the entire process
Andreas Heinzel, for inspiration regarding architectural- and software-related topics
The Delta4 GmbH team for providing helpful inputs

Reference
Matthias Ley, Andreas Heinzel, Lucas Fillinger, Klaus Kratochwill, Paul Perco, OntoloViz: a GUI for interactive visualization of ranked disease or drug lists using the MeSH and ATC ontologies, Bioinformatics Advances, 2023; vbad113, https://doi.org/10.1093/bioadv/vbad113