Open serpei opened 1 year ago
The snakemake_config.yaml is intended to stay in the IRIS/ folder. If you want to run IRIS multiple times in parallel you could create a separate install of IRIS in a different folder. I think another option is to just put a new copy of the IRIS code in a new folder and then set these config paths to point to the main installed version of IRIS: https://github.com/Xinglab/IRIS/blob/v2.0.1/snakemake_config.yaml#L105
If you have multiple runs at the same time then they should have different run_name
config values
To run all steps you should set run_all_modules: true
. If you want to use tissue_matched_normal or tumor references then you should fill out all the config values for that reference group: https://github.com/Xinglab/IRIS/blob/v2.0.1/snakemake_config.yaml#L61
At least one of tissue_matched_normal or normal is required
There are separate output files for the comparison against the tissue_matched_normal (tier 1) and the comparison against all 3 of tissue_matched_normal, tumor, and normal (tier 3): https://github.com/Xinglab/IRIS/tree/v2.0.1#example-output
When you run the pipeline it will add a new directory to IRIS_data/db using the run_name from the config. After running the pipeline you can then use the results in a future run as one of the reference_group_names
From https://github.com/Xinglab/IRIS/blob/v2.0.1/example/parameter_file_description.txt#L40
Removes the AS events that are error-prone due to artifacts
Here's the example file https://github.com/Xinglab/IRIS/blob/v2.0.1/IRIS/data/blocklist.brain_2020.txt
and 7. From https://github.com/Xinglab/IRIS/blob/v2.0.1/example/parameter_file_description.txt#L36
Comparison mode & statistical test type: 'group' mode (number of input samples >=2) and 'individual mode' (number of input sample =1) are provided. 'group' mode is default and recommended; for PSI-based tests, 'parametric' and 'nonparametric' tests are supported. 'parametric' is default
No maximum
The snakemake does not use the novelSS parameter
The snakemake only supports one event type at a time. If you want output for each event type then you need to run multiple times
Thank you so much for your explanations! Given that I would like to consider all events types and also novelSS I think I have to use the single functions to build a pipeline. Do you agree? Given so, the single functions support multithreading and I can fix number of core to be using in each of them? Thank you again, Serena
Building your own pipeline from the individual functions is reasonable. Depending on how much you want to change, you could try modifying the provided snakemake workflow instead of building a new pipeline from scratch
The single functions use multithreading, but they don't take the number of cores as a parameter. For example: https://github.com/Xinglab/IRIS/blob/v2.0.1/snakemake_config.yaml#L7 https://github.com/Xinglab/IRIS/blob/v2.0.1/IRIS/IRIS_process_rnaseq.py#L13 https://github.com/Xinglab/IRIS/blob/v2.0.1/IRIS/IRIS_process_rnaseq.py#L27
You can edit the files to change the number of threads
Excuse me for the late response. Thank you again!
Hi, thank you for your super-interesting tool.
I have some questions about the snakemake_config.yaml (If I plan to run all pipeline together using snakemake)
Sorry to bother you, thank you, Serena