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Prepare your illumina reads before DADA2 pipeline

written by Gian M N Benucci, PhD
email: [email protected]
May 29, 2024

This pipeline is based upon work supported by the Great Lakes Bioenergy Research Center, U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under award DE-SC0018409

Warning

To use DADAprep just clone the directory usign SSH

git clone [email protected]:Gian77/DADAprep.git

Note

• This pipeline run using SLURM (please see bove). Resourches of each individual job scripts present in the /mnt/home/benucci/DADAprep/code/ directory MUST be adjusted to the amount of data you want to run for each pipeline run. In particular the parameters below.

#SBATCH --time=00:10:00
#SBATCH --nodes=1
#SBATCH --ntasks=1
#SBATCH --cpus-per-task=8
#SBATCH --mem=16G

• Data MUST be demultiplexed and all R1 and R2 read files copied in the $project_dir/rawdata/ directory, alongside a md5sum checksum file names md5.txt.
• The individual scripts in the code directory include the buy-in node priority #SBATCH -A shade-cole-bonito. If you do not have access to those priority nodes please remove that line in the individual scripts.
• Subdirectories such as outputs and slurms are part of the workflow, and should be left as they are.
• Please check the config file for options. A few script are additional and are can be avoided to save time.
  
• The directory called condaenvs contain all the yml files you can use to recreate the exat conda environments used to develop DADAprep. To create a conda environment based on a recipe you can do: conda env create -f environment-name.yml.
• Find a good PATH for your Phix genome database, mine is phix_db="/mnt/research/ShadeLab/Benucci/databases/phix_index/my_phix".
• marked if you want your filtered readse to be paried or not using the paired="yes" option in the config.yaml file.
• set your primers. For example: fwd_primer="CCTACGGGAGGCAGCAG" and rev_primer="GGACTACHVGGGTWTCTAAT", again, in your config file.

Run DADAprep using sh DADAprep.sh

DADAprep output will be a tar.gz file in the main directory named e.g. out_DADAprep_29-05-2024.tar.gz