ARGs_OAP

This repository was created by Xiaole Yin (xiaole99) and is currently maintained by Xi Chen (xinhec). The goal is to make args_oap faster, and easier to run.

If you have any questions, please create an issue, or contact Xiaole Yin ([email protected]).

More about the SARG database: https://smile.hku.hk/ARGs/Indexing, and the change logs: CHANGELOG.md.

Installation

Conda (macOS/Linux):

conda install -c bioconda -c conda-forge args_oap

We suggest to create a new conda environment (here use -n args_oap as an example) to avoid potential conflicts of dependencies:

conda create -n args_oap -c bioconda -c conda-forge args_oap
conda activate args_oap

If your OS satisfies all the dependencies (python>=3.7, diamond>=2.0.15, bwa>=0.7.17, blast>=2.12, samtools>=1.15), then build from source:

git clone https://github.com/xinehc/args_oap.git
cd args_oap
python setup.py install  # use python3 if needed

Example

Two example fasta files (100k paired-end reads, 100 bp each) can be found here. The zipped file can be downloaded manually or using wget:

# conda install wget
wget https://dl.dropboxusercontent.com/s/pqgftlo24rfc2rd/example.tar.gz
tar -xvf example.tar.gz
cd example

# conda activate args_oap
args_oap stage_one -i input -o output -f fa -t 8
args_oap stage_two -i output -t 8

After stage_one, a metadata.txt file can be found in output. It summarizes the estimated 16S and cell copy numbers in each sample, for example:

sample	nRead	n16S	nCell
STAS	200000	8.229297879794053	3.1472376316269055
SWHAS104	200000	7.009547807125172	3.487830355315917

After stage_two, the normalized ARGs copies per 16S/cells or hits per million reads will be shown in several *_normalized_*.txt files. For example, normalized_cell.type means:

• normalized_cell - normalized against cell number
• type - type of ARGs (the hierarchy in the SARG database is type -> subtype -> gene)

type	STAS	SWHAS104
aminoglycoside	0.04236519416057223	0.1411521328969608
bacitracin	0.03724412673456899	0.07331127852930945
beta_lactam	0.0	0.14920548807040623
macrolide-lincosamide-streptogramin	0.0	0.02404226144950743
multidrug	0.012948920209830746	0.19382414709324317
mupirocin	0.007757298735456341	0.009159215245515702
quinolone	0.37832158835366747	0.08842494718334318
sulfonamide	0.035174054192357015	0.1368367904789564
tetracycline	0.012183242185747383	0.09987284037027115

Output file extracted.filtered.fa contains all filtered ARG-like sequences after stage_two. blastout.filtered.txt is the metadata of these sequences.

De-contamination:

Before running ARGs-OAP, a de-contamination processes is recommended to secure clean prokaryotic reads. This includes the removal of genomic sequences from hosts (e.g., human), and from fungal sources. This step is critical to avoid potential biases in the calculation of cell numbers which relies on the identification of essential single copy marker genes.

Notes

(optional) Single/Paired end files

If you use paired-end files, please make sure the forward/reverse reads end with _1|_2, _R1|_R2 or _fwd|_rev (followed by .format, see -f, .gz optional), otherwise they will not be considered as a single sample. Example for fasta format files (-f fa):

STAS
   ├── STAS_1.fa
   └── STAS_2.fa.gz
SWHAS104
   ├── SWHAS104_R1.fa
   └── SWHAS104_R2.fa.gz

(optional) Customized database/structures

To use customized databases (e.g. mobile genetic elements or heave metal resistant genes), you need to prepare two files:

1. nucleotide sequences or amino acid (protein) sequences database (e.g. database.fasta)
2. hierarchical structure file (e.g. structure.txt)

The database should be indexed manually (protein or nucleotide, in fasta):

## protein or nucleotide
args_oap make_db -i database.fasta

The structure file structure.txt should be tab-separated and the first column the sequences ID of database.fasta (please note that the sequence ID cannot contain space, tab and other irregular char such as forward slash). At lease one column (level 1) is required. For the one column (level 1) case, you may construct the structure file using:

echo '>level1' | cat - database.fasta | grep '^>' | cut -d ' ' -f 1 | cut -c2- > structure.txt

One example of the database.fasta and structure.txt is :

database.fasta:

    >seq1
    ACGT...
    >seq2
    TGCA...

structure.txt:

    level1    level2    level3
    seq1    subtype1    type1
    seq2    subtype2    type2

To run args_oap with customized database:

args_oap stage_one -i input -o output -f fa -t 8 --database database.fasta
args_oap stage_two -i output -t 8 --database database.fasta --structure1 structure.txt

(optional) Stage two pipeline on Galaxy system and download results

(The online version currently does not support SARG v3.0, please use the local version at this moment.)

Go to http://smile.hku.hk/SARGs and using the module ARG_OAP.

1. Using ARG_OAP -> Upload Files module to upload the extracted fasta file and meta_data_online.txt file generated in stage one into Galaxy
2. Click ARG_OAP and Ublast_stagetwo, select your uploaded files
3. For "Column in Metadata:" chose the column you want to classify your samples (default: 3)

Click Execute and you can find four output files for your information

After a while or so, you will notice that their are four files generated for your information.

File 1 and 2: PcoA figures of your samples and other environment samples generated by ARGs abundance matrix normalization to 16S reads number and cell number
File 3 and 4: Other tabular mother tables which including the profile of ARGs type and sub type information, as long as with other environment samples mother table. File3 results of ARGs abundance normalization against 16S reads number; File 4 results of ARGs abundance normalization against cell number

There are some questions raised by users, please refer to the FAQ for details. To run ARG OAP locally, users should download the source code into local computer system (Unix/Linux). Users can upload the generated files for stage two onto our Galaxy analysis platform (http://smile.hku.hk/SARGs) or use the local version of stage two script.

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Notice:

This tools only provide the required scripts for ARGs-OAP 3.0 pipeline

This pipeline is distributed in the hope to achieve the aim of management of antibiotic resistant genes in environment, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.This pipeline is only allowed to be used for non-commercial and academic purpose.

The SARG database is distributed only freely used for academic purpose, any commercial use should require the agreement from the developer team.