GMHI2: Gut Microbiome Health Index 2

Description

Gut Microbiome Health Index 2 (GMHI2) is a robust index for evaluating health status based on the species-level taxonomic profile of a stool shotgun metagenome (gut microbiome) sample.

Installation

To avoid dependency conflicts, create an isolated conda environment and install gmhi2

Install via conda

conda create --name gmhi2_env -c danielchang2002 python=3.7 gmhi2

Activate environment

conda activate gmhi2_env

Usage

usage: gmhi2 [-h] [-o OUTPUT] --fastq1 FASTQ1 --fastq2 FASTQ2

DESCRIPTION:
GMHI2 version 1.0
Gut Microbiome Health Index 2 (GMHI2) is a robust index for evaluating 
health status based on the species-level taxonomic profile of a stool 
shotgun metagenome (gut microbiome) sample.

AUTHORS:
Daniel Chang, Vinod Gupta, Jaeyun Sung

USAGE:
GMHI2 is a pipeline that takes as input two raw fastq files generated 
from a paired end sequence, performs quality control, estimates microbial 
abundances, and returns as output a health index score.

* Profiling a metagenome from raw reads:
$ gmhi2 --fastq1 metagenome1.fastq --fastq2 metagenome2.fastq

optional arguments:
  -h, --help            show this help message and exit
  -o OUTPUT, --output OUTPUT
                        Output file name

required named arguments:
  --fastq1 FASTQ1       first input fastq file
  --fastq2 FASTQ2       second input fastq file

Example

Directory structure:

.
├── metagenome1.fastq
└── metagenome2.fastq

Command:

gmhi2 --fastq1 metagenome1.fastq --fastq2 metagenome2.fastq -o GMHI2.txt

Result:

.
├── GMHI2.txt
├── abundance.txt
├── metagenome1.fastq
└── metagenome2.fastq

where GMHI2.txt is a text file with a single line containing the health index score of the metagenome, and abundance.txt is a tsv containing the estimated microbial abundances.

Runtime

Runtime depends on the size of the input metagenome and the system specs.

On a 2019 MacBook Pro with a 2.3 GHz 8-Core Intel Core i9 processor and 16GB of RAM, a single run of gmhi2 on an input metagenome of 4 GB takes 29 minutes.