fastHaN

A fast and scalable program for constructing haplotype network for large-sample sequence data sets.

Description

fastHaN is a fast and scalable program for constructing haplotype networks for large samples
fastHaN can implement the minimum joint network (MJN) and the Templeton-Crandall-Sing (TCS) algorithms
The implementation in single-thread mode is much faster than the existing softwares
Furthermore, fastHaN enables multi-threaded mode with good scalability

Quick start guide

For Linux:（Please ensure that your computer system supports the avx instruction set, or the program will exit with an error.）
1. download the software and grant execution permissions
   chmod +x fastHaN_linux

2. run the test data (Example/Test1000.phy.gz) with mjn algorithm
   ./fastHaN_linux mjn -i Example/Test1000.phy.gz -t 8 -o Test1000

For windows:（Please ensure that your computer system supports the avx instruction set, or the program will exit with an error.）
1. run in the CMD window
    fastHaN_win.exe mjn -i Example/Test1000.phy.gz -t 8 -o Test1000

Usage

fastHaN [Options]

Options:
    original_tcs        original TCS algorithm (Clement et al., 2000)
    modified_tcs        optimization of TCS implementated by PopART (Leigh, 2015)
    msn                 optimization of MSN implementated by PopART
    mjn                 optimization of MJN implementated by PopART (Bandelt, et al., 1999)

Options

original_tcs

usage: fastHaN original_tcs [arguments]

input:
    -i    input phylip format file
options:
    -t    (int)thread number(default:8)
    -a    (int)is mark the sites which contains ambiguous base, 1:mask, 0:not(default:0)
    -m    (int)is merge intermediate vertex, 1:merge, 0:not:(default:0)
output:
    -o    path prefix of the output graph file (GML and json format)

modified_tcs

usage: fastHaN modified_tcs [arguments]

input:
    -i    input phylip format file
options:
    -t    (int)thread number(default:8)
output:
    -o    path prefix of the output graph file (GML and json format)

msn

usage: fastHaN msn [arguments]
     
input:
    -i    input phylip format file
options:
    -e    (int)epsilon(default:0)
output:
    -o    path prefix of the output graph file (GML and json format)

mjn

usage: fastHaN mjn [arguments]
     
input:
    -i    input phylip format file
options:
    -t    (int)thread number(default:8)
    -e    (int)epsilon(default:0)
output:
    -o    path prefix of the output graph file (GML and json format)

Input and Output

Input file (PHYLIP format)

3 75
Hap385899 GATCTGTTCTCTAAACGAACTTGAAAATCTGTGTGGCTGTCACTCGGCTGCATGCTTAGTGCACTCACGCAGTAT
Hap279195 GATCTGTTCTCTAAACGAACTTTAATATCTGTGTGGCTGTCACTCGGCTGCATGCTTAGTGCACTCACGCAGTAT
Hap871484 GATCTGTTCTCTAAACGAACTTTAAAATCTGTGTGGCTGTCACTCGGCTGCACGCTTAGTGCACTCACGCAGTAT

3: the number of haplotypes
75: the number of characters for each haplotype
Hap385899: the haplotype name
GATCTG...GTAT: the sequence of the haplotype Hap385899

Output file (GML and Json format)

Both GML file and Json file represent the constructed haplotype network

GML file is used as the input of tcsBU software to visualize the haplotye network
Json file is used to prepare color theme for the constructed haplotype network (refer to section of 'Visualization')

Visualization

After constructing the haplotype network with fastHaN, we need to use the software tcsBU to visualize it.
The tcsBU (https://github.com/sairum/tcsBU) is a browser-based JavaScript program, which is included in fastHaN's package. All you need to do is unzip tcsBU.zip and double-click the index.html file.
In order to show the composition of haplotypes within one node, you need to provide a META file (two column) that specifies the group information (eg. country, city, et) for each haplotype.

META file format (given by the user)

there is an example file (Test167.meta) in the directory of 'fastHaN/Visualization/Example'

Hap6825391      SouthAfrica
Hap6825397      SouthAfrica
Hap6825546      Austria
Hap6795850      SouthAfrica
Hap6795842      SouthAfrica

Hap6825391: the haplotype name, which must be consistent with that in the phylip file
SouthAfrican: the group information of the haplotye Hap6825391

Generate config files for tcsBU

You can use the Python script of GenNetworkConfig.py to generate two config files required by tcsBU.
You can also manually generate the two config files by referring to the file format below (*_groupconf.csv and *_hapconf.csv)

# generate the config files
python GenNetworkConfig.py Test167.json Test167.meta Test167Conf

# Two config files will be generaged by above command
1. Test167Conf_groupconf.csv
2. Test167Conf_hapconf.csv

1. Test167Conf_groupconf.csv (3 column, semicolon separation)

SouthAfrica;#4C3D35;none
Austria;#D56234;none
Botswana;#DCBD4D;none

1-th: group name, eg. SouthAfrica
2-th: random colors generated by GenNetworkConfig.py, eg. #4C3D35
3-th: fixed column with a value of 'none'

2. Test167Conf_hapconf.csv (2 column, semicolon separation)

Hap6825390;SouthAfrica
Hap6825391;SouthAfrica
Hap6825397;SouthAfrica
Hap6825546;Austria
Hap6795850;SouthAfrica
Hap6795842;SouthAfrica

1-th: the haplotype name, which must be consistent with that in the phylip file
2-th: group name for each haplotype

Reference

Chi, L., Zhang, X., Xue, Y., & Chen, H. (2023). fastHaN: a fast and scalable program for constructing haplotype network for large-sample sequences. Molecular Ecology Resources, 00, 1– 5.
Bandelt, H.J., Forster, P., and Rohl, A. (1999). Median-joining networks for inferring intraspecific phylogenies. Mol Biol Evol 16, 37-48.
Clement, M., Posada, D., and Crandall, K.A. (2000). TCS: a computer program to estimate gene genealogies. Mol Ecol 9, 1657-1659.
Leigh, J.W. (2015). POPART: full-feature software for haplotype network construction. Methods in Ecology and Evolution.
Murias dos Santos, A., Cabezas, M.P., Tavares, A.I., Xavier, R., and Branco, M. (2016). tcsBU: a tool to extend TCS network layout and visualization. Bioinformatics 32, 627-628.

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