ONT16SAnalysis

This is a work in progress pipeline to process full-length 16s rRNA data from ONT.

Basecalling

To run the basecalling:

snakemake --use-conda -c 16 --snakefile workflow/Basecalling.smk -n #remove -n to start the job

Tutorial

Step 1: Clone the workflow

Clone this repository to your local system, into the place where you want to perform the data analysis.

git clone git@github.com:matinnuhamunada/ONT_16S_Analysis.git
cd ONT_16S_Analysis

Step 2: Prepare the input data

Structure your raw read data from ONT to look like this:

data
└── raw
    ├── fastq_pass-20230814T144538Z-001.zip
    ├── fastq_pass
    │   ├── barcode01
    │   │   └── FAW91967_pass_barcode01_a80fe2bd_f92c8855_28.fastq.gz
...

Step 3: Configure workflow

Setting Up Your Samples Information

Configure the workflow according to your needs via editing the files in the config/ folder. Adjust config.yaml to configure the workflow execution, and samples.tsv to specify the samples for analysis. The file units.tsv contains the location of the paired illumina and nanopore reads for each sample.

samples.tsv example:

sample	description
barcode01	Stool

units.tsv example:

sample	unit	illumina_reads	nanopore_reads
barcode01	1		data/raw/GCF_000012125.1

Step 3: Install Snakemake

Installing Snakemake using Mamba is advised. In case you don’t use Mambaforge you can always install Mamba into any other Conda-based Python distribution with:

conda install -n base -c conda-forge mamba

Then install Snakemake with:

mamba create -c conda-forge -c bioconda -c panoptes-organization -n snakemake snakemake panoptes-ui

For installation details, see the instructions in the Snakemake documentation.

Step 4: Executing the workflow

Activate the conda environment:

conda activate snakemake

Run panoptes to monitor jobs:

tmux new-session -A -s panoptes \; send -t panoptes "conda activate snakemake && panoptes" ENTER \; detach -s panoptes # run panoptes in background at http://127.0.0.1:5000

Do a dry-run:

snakemake --use-conda --cores $N --wms-monitor http://127.0.0.1:5000 -n

We can then open http://127.0.0.1:5000 to monitor our jobs

See the Snakemake documentation for further snakemake CLI details.

Data Analysis

Install qiime2:

mamba env create -n qiime2-amplicon-2024.5 --file https://data.qiime2.org/distro/amplicon/qiime2-amplicon-2024.5-py39-linux-conda.yml

Activate qiime2:

mamba activate qiime2-amplicon-2024.5