HyDRA (Hybrid De novo Assembly and Resistance Analysis) is a state-of-the-art and user-friendly Snakemake workflow designed for the analysis of WGS data. It integrates multiple bioinformatics tools and algorithms to facilitate key steps in WGS analysis, including quality control of sequencing reads, hybrid assembly, taxonomic classification, gene prediction and annotation as well as identification of plasmids and antibiotic resistance genes (ARGs).
Comprehensive Quality Control: Involves a thorough assessment and filtering of sequencing data to identify and remove errors, ensuring high-quality and reliable data for downstream analysis.
Hybrid Assembly: Utilize short and long sequencing reads in combination to create more accurate and complete genome assemblies, leveraging the strengths of both read types.
Taxonomic Classification: Apply advanced taxonomic classification methods to assign taxonomic labels to the isolate.
Gene Prediction and Annotation: Utilizing methods to identify gene locations within a genome assembly and annotating their functions, enabling to understand the biological roles and interactions of the genes.
Plasmid Identification: Involves methods to detect and characterize plasmid DNA within a genomic dataset, differentiating it from chromosomal DNA to study its role in horizontal gene transfer and other functions.
Antibiotic Resistance Gene Identification: Perform in-depth analysis to detect and characterize antibiotic resistance genes within the sample, providing valuable insights into antimicrobial resistance profiles.
%%{init: {
'theme':'base',
'themeVariables': {
'secondaryColor': '#fff',
'tertiaryColor': '#fff',
'tertiaryBorderColor' : '#fff'}
}}%%
flowchart TB;
subgraph " "
direction TB
%% Nodes
A[/short reads/]
B[/long reads/]
C["<b>Quality Control</b> <br> <i>fastp, FastQC, Porechop, Chopper<i>"]
D[/MultiQC report/]
E["<b>Hybrid <i>de novo<i> Assembly</b> <br> <i>Unicycler</i>"]
F["<b>Assembly Control</b> <br> <i>CheckM2, QUAST<i>"]
G[/Genome Assembly/]
H["<b>Gene Prediction & Annotation</b> <br> <i>Prokka<i>"]
I["<b>Taxonomic Classification</b> <br> <i>GTDB-Tk<i>"]
J["<b>Plasmid Identification</b> <br> <i>geNomad<i>"]
K["<b>Resistance Analysis</b> <br> <i>CARD & RGI<i>"]
%% input & output node design
classDef in_output fill:#fff,stroke:#cde498,stroke-width:4px
class A,B,D,G in_output
%% rule node design
classDef rule fill:#cde498,stroke:#000
class C,E,F,H,I,J,K rule
%% Node links
A --> C
B --> C
C --> E
C --- D
E --> F
E ---- G
G --> H
G --> I
G --> J
G --> K
end
To prepare the workflow
- Clone it to your desired working directory via git or your preferred IDE
- Edit the
config/config.yaml
file:- Specify the run date or project name (
run_name
)
- Specify the run date or project name (
- Provide a sample information in the
config/pep/samples.csv
file with keeping the header and format as.csv
:
sample_name,long,short1,short2
sample1, path/to/your/long_read/fastq/sample1.fastq.gz,path/to/your/short_read /fastq/sample1_R1.fastq.gz,path/to/your/short_read /fastq/sample1_R2.fastq.gz
snakemake --use-conda --cores all
The usage of this workflow is described in the Snakemake Workflow Catalog.
HyDRA is released under the BSD-2 Clause. Please review the license file for more details.
For any questions, or feedback, please contact the project maintainer at [email protected]. We appreciate your input and support in using and improving HyDRA.
CARD & RGI
Checkm2
Chopper
fastp
FastQC
geNomad
minimap2
MultiQC
Nanoplot
pandas
PLM-ARG
Porechop_ABI
Prokka
QUAST
samtools
Unicycler
A paper is on its way. If you use HyDRA in your work before the paper, then please consider citing this GitHub.