Adapted from Patricia Baldrich's pipeline

Script for prepDE.py3 was retrieved from https://ccb.jhu.edu/software/stringtie/dl/prepDE.py3 with only minor changes made

This preprocess pipeline is specifically for paired end reads, so you must have 2 reads per sample.

git clone https://github.com/tellmathieu/RNAseqPreprocess.git 

• a) install mamba if you don't already have it - you'll have to go through the installation process or do a command like module load mamba

wget "https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-$(uname)-$(uname -m).sh" bash Miniforge3-$(uname)-$(uname -m).sh 

• b) Initialize mamba and set up an environment - this can take 5-10 minutes - hisat2 and stringtie need to be these specific versions for recreating our results from original pipeline

source ~/.bashrc #or you can log out and then log back in mamba create -c conda-forge -c bioconda -y -n preProcessRNAseq snakemake=8.15.2 hisat2=2.2.1 samtools=1.20 stringtie=2.1.4 mamba activate preProcessRNAseq 

• {sample_name}_R1.fastq or {sample_name}_R1.fq
• {sample_name}_R2.fastq or {sample_name}_R2.fq

The {sample_name} is what you choose (don't put any spaces in this name). The files must have the suffixes, including the read number (1 or 2).

An example of how my files were named is:

• Col0_AWF_NT_R4_R1.fastq
• Col0_AWF_NT_R4_R2.fastq

cd RNAseqPreprocess nano preprocess_RNAseq_DE.smk 

In the nano editor (or whatever your preferred editor is), change the following 4 variables:

############# --- INPUT VARIABLES --- ############# ### --- Change file paths here to your data --- ### ##### --- Full filepath starting with "/"" --- #### ### --- No slashes at the end of a filepath --- ### fastqDirectory="/home/RNAseqAnalysis/fastq" genome="/home/RNAseqAnalysis/input/Ath_genome.fa" annotation="/home/RNAseqAnalysis/input/Ath_genes.gff" threads=20 

Make sure you have read/write privileges in these files.

The fastqDirectory variable is the folder where you have all your fastq files (with the naming convention I specified).

The genome variable is the filepath to the .fasta or .fa file you are using to map the RNAseq data against.

The annotation variable is the filepath to the .gff file you are using to map the RNAseq data against. You usually get this from where you get the genome file from.

The threads variable is for the computer to know how many threads to allocate each step. More threads usually means its quicker, but computer systems have limits, so that's why I have you specify it.

Now, you're ready to run the pipeline. Most of the time is taken with mapping the RNAseq (fastq) files to the genome and annotation. With 12 samples and 20 threads, it took a little more than a day for me. I usually run this using the screen software (so you can detach but the command continues to run).

The -j 20 specification is how many threads I told the computer to allocate to this job. I made it the same as what I specified in the file itself, so each "job" the computer runs gets the full 20 threads.

snakemake --snakefile preprocess_RNAseq_DE.smk -j 20 -p