DUGMO

Detection of Unknown Genetically Modified Organisms

Introduction

DUGMO is a bioinformatics pipeline for the detection of GMOs, including unknown GMOs, based on Illumina paired-end sequencing data. In first steps, coding sequences (CDS) are aligned through two successive BLASTN against the host pangenome with relevant tuned parameters to discriminate CDSs belonging to the wild genome (wgCDS) from potential GMO coding sequences (pgmCDS). Then, Bray-Curtis distances are calculated between the wgCDSs and the pgmCDSs based on the difference of genomic vocabulary between these two sets. Finally, two machine learning methods, namely random forest and generalized linear model, are carried out to target true GMO CDS(s).

Installation with conda

Git glone

git clone https://github.com/jhurel/DUGMO.git
cd DUGMO

Create a conda environnement

conda create -n DUGMO snakemake
conda activate DUGMO

Params in configDUGMO.json

Params name	Description
R1	Input file Read 1 in fq or fq.gz format
R2	Input file Read 2 in fq or fq.gz format
RefGenome	Input file of reference genome in fasta format
PangenomeCDS	Input file of pangenome CDS in .fa.gz format
PangenomeWhole	Input file of pangenome whole genome in .fa.gz format
outputFolder	path of output folder for all results
threads	Number of threads to use (default: 10)

Quick start

Launch the snakemake workflow

snakemake -rpk --use-conda

Output files

Foldername	Description
Cleaning_pipeline	Cleaning pipeline with Shovill, Trimmomatic, BWA, Bowtie2, Blast and Prokka
DataBankGMO	Databank files
GMO	GMO potential files
HostGenome	Host genome files
MachineLearning	Results at the final step
Rmes	Rmes output files