Hi,
In the example they give in their GitHub (https://github.com/Xinglab/rmats-turbo/blob/v4.3.0/README.md):
They have 2 sample groups with 2 BAM files per group. They create txt files that will be used to pass this grouping of inputs to rMATS. The expected format is , to separate replicates.
Name of txt file: /path/to/b1.txt
Contents of txt file: /path/to/1_1.bam,/path/to/1_2.bam
and
Name of txt file: /path/to/b2.txt
Contents of txt file: /path/to/2_1.bam,/path/to/2_2.bam
I am not sure whether they actually require you to name the txt file with the actual path. You can try just naming them b1 and b2, and using the pathway when you use rMATS. You can use this next step to get the pathway, either way:
So, here you will make two text files. First, start off by creating a txt file called "b1". Then, make a second txt file called "b2". As an example, I'll create two txt files with these names in a new folder called "flowering_plants_transcriptomics" in my Documents folder of my computer. Now, if you right click on one of the txt files and go to "Properties", you can find the location of this file in your computer:
Now, copy and paste this path into the name of your txt file. Mine would be C/Users/mpeko/Documents/flowering_plant_transcriptomics/b1.txt. Repeat this process for your b2.
Within each txt file, you will similarly give the paths of your associated BAM files, with a "," to separate them.
You will use these txt files as your input for rMATS:
python rmats.py --b1 /path/to/b1.txt --b2 /path/to/b2.txt --gtf /path/to/the.gtf -t paired --readLength 50 --nthread 4 --od /path/to/output --tmp /path/to/tmp_output
From https://github.com/Xinglab/rmats-turbo/blob/v4.3.0/README.md#all-arguments to answer your next question about b1 and b2 parameters:
b1 (which is the first txt file we created):
A text file containing a comma separated list of the
BAM files for sample_1. (Only if using BAM)
b2 (which is the second txt file we created):
A text file containing a comma separated list of the
BAM files for sample_2. (Only if using BAM)
This last link I just gave has several tips by the package developers, and they also include a sample data set that might be helpful for you to practice on before you start your actual analysis: https://sourceforge.net/projects/rnaseq-mats/files/MATS/testData.tgz/download.