Using trim-mgi-adapters on Deepthought.

Note: Deepthought is Flinders' HPC, and is pretty much a standard HPC running slurm. These instructions may work for you, but they may not.

This assumes that you have a directory called fastq with your R1 and R2 reads, and that you want the trimmed fastq files in a directory called fastq\_trimmed. We will also put the reports of which sequences find which files into a directory called fastq_adapter_matches. Finally, we use a directory called trimming_slurm for the slurm output files.

Step 1. Clone the repo and build the code

In your account, clone the repository and build all the code. No modules are needed for this:

git clone https://github.com/linsalrob/mgi-adapters.git
cd mgi-adapters
make all

Step 2. Create a file with all the R1 reads, and just their names

cd path/where/sequences/are
find fastq -type f -name \*R1* -printf "%f\n" > R1_reads.txt

Step 3. Create a directory for the slurm output files

mkdir trimming_slurm

Note: If you don't do this, the sbatch command below will run normally and you will think everything is fine, although it finishes very quickly and has not done anything!

Step 4. Find out how many R1 reads we have

READS=$(wc -l R1_reads.txt | awk '{print $1}');

Step 5. Submit the array job to process all those reads.

Note that the slurm script makes the directories for fastq_trimmed and fastq_adapter_matches. It also handles both the R1 and R2 files.

sbatch --array=1-$READS:1 ~/GitHubs/mgi-adapters/deepthought/trim_array.slurm

Wait for the results!

Here is the whole command in one line, so you can just copy and paste it!

mkdir trimming_slurm; find fastq -type f -name \*R1* -printf "%f\n" > R1_reads.txt; READS=$(wc -l R1_reads.txt | awk '{print $1}'); sbatch --array=1-$READS:1 ~/GitHubs/mgi-adapters/deepthought/trim_array.slurm