FuncTree-CLI

FuncTree-CLI is a command-line application, which allows user to visualize, customize, and compute statistical test to understand the biological functionality of their omics data. FuncTree-CLI allows user to map their omics data on to a pre-defined treemap, which is based on the KEGG or other hierarchical functional databases. This allows user to quickly and comprehensively understand the functional potential of their data, and to develop further hypothesis and scientific insights.

Data Visualization

FuncTree-CLI creates hierarchical visualization. In the treemap nodes represent particular biological functions and edges represent hierarchical relationships between the functions.

Requirements

• Node.js
• Python

Installation

You can quickly install FuncTree-CLI on your system by using npm:

$ npm install --global functree-cli

Usage

Overview

Basic usage and available commands and options are listed below:

Usage: functree [command] [options...]

Commands:
  get [options...]     Get tree structure data from database
  stats [options...]   Perform statistical analysis
  create [options...]  Create visualization

Options:
  --no-color     Disable colored output                                                    [boolean]
  --show-config  Show default configuration value                                          [boolean]
  --help         Show help                                                                 [boolean]
  --version      Show version number                                                       [boolean]

Get tree structure data from database

Before creating a visualization, you need to prepare tree structure data for data mapping. FuncTree-CLI provides the simple way to get tree structure data from KEGG in the following command.

$ functree get -d kegg -o kegg.json

Or, you can use your own tree structure data for drawing treemap. It must be in the JSON format and have the structure corresponded to the following example.

{
  "id": "00001",
  "name": "path:map00010",
  "label": "Glycolysis / Gluconeogenesis",
  "children": [
    {
      "id": "00002",
      "name": "md:M00001",
      "label": "Glycolysis (Embden-Meyerhof pathway), glucose => pyruvate",
      "children": [
        {
          "id": "00003",
          "name": "ko:K00844",
          "label": "HK; hexokinase [EC:2.7.1.1]"
        },
        {
          "id": "00004",
          "name": "ko:K12407",
          "label": "GCK; glucokinase [EC:2.7.1.2]"
        }
      ]
    }
  ]
}

Perform statistical analysis

This feature consists of following two steps:

1. Evaluate functionality: If your omics data is only annotated by KEGG Orthology, you can evaluate functionality for all functional categories defined by input tree structure data (i.e. module, pathway etc.). This feature requires KO-annotated abundance table which is separated by tabs.

   # This is comment
   	sample1	sample2	sample3
   ko:K00001	0.000218080750998678	0.000292011269409172	0.000183811396397214
   ko:K00002	1.66822340270918e-05	2.9109921924858197e-05	2.9970461739666497e-05
   ko:K00003	0.00010209658248844201	0.000267883926930514	0.00034744353401109
   ko:K00004	2.55973088845531e-06	1.1145349476428498e-06	7.774328858319991e-06
   ko:K00005	0.000104872989966464	7.822164009693009e-05	5.73637517684323e-05
   

2. Perform comparison between two groups: If necessary, you can compute hypothesis test for all functional categories defined by input tree structure file (i.e. module, pathway etc.). This feature requires two tab-separated tables calculated by the above feature.

Example usage and available options and are listed below:

# Evaluate functionality - Mean
$ functree stats -t kegg.json -m mean -i ko_abundance.tsv -o all_abundance.tsv

# Perform comparison between two groups - Mann-Whitney U test
$ functree stats -t kegg.json -m mannwhitneyu -i all_abundance_1.tsv all_abundance_2.tsv -o all_pvalue.tsv

Option	Long option	Description
-i	--input	Path to input abundance table(s)
-o	--output	Output result to file
-t	--tree	Path to tree structure data JSON file
-m	--method	Specify statistical analysis method
-c	--config	Path to configuration JSON file

Create visualization

This feature is the main part of FuncTree-CLI. This helps you create a insightful visualization with your own data. If necessary, you can specify output image format type (SVG (default), PNG or interactive HTML) with -f, --format option.

Example usage and available options and are listed below:

$ functree create -t kegg.json -i all_abundance.tsv -o image.png -f png

Option	Long option	Description
-t	--theme	Specify theme of visualization
-i	--input	Path to input abundance table
-o	--output	Output visualization image to file
-t	--tree	Path to tree structure data JSON file
-f	--format	Specify output format type
-c	--config	Path to configuration JSON file

Building

1. Clone this repository.
2. Run npm install to install the dependencies.
3. Run npm run build to compile the ES6 codes (src/*.js).

Link

• FuncTree 2 - http://www.bioviz.tokyo/functree2/

Reference

• Uchiyama T, Irie M, Mori H, Kurokawa K, Yamada T. FuncTree: Functional Analysis and Visualization for Large-Scale Omics Data. PLoS One. 2015 May 14;10(5):e0126967. doi: 10.1371/journal.pone.0126967. eCollection 2015. PubMed PMID: 25974630; PubMed Central PMCID: PMC4431737.

License

See LICENSE file.