Thanks for sharing the screenshots @Dongqi_Xie !!
On the tool form, the select field will list all potential input datasets. These will always be datasets present in the active history and with an assigned datatype that matches one of the “accepted datatypes” for that input field.
Then, from the listing, you can select the input datasets to actually use by clicking on them from the listing pull-down menu.
And to review the inputs and parameters that were applied for a job, reviewing the job’s Details view will have a table of those settings. You have this in one of your screenshots. This is a screenshot of your screenshot of the relevant section:
-
You are also using a
gtfdataset that was sourced from Gencode that is based on the Homo Sapiens GRCh38 hg38 assembly. This is your reference annotation. -
It seems you have selected two replicates from two different samples for a total of four
bamdataset files.- We can’t see which reference genome you used for the mapping step to create the
bams. I’m guessing this was a custom genomefastafile from the history? This should be fine. - If it was the assembly from Gencode based on the same release as the annotation, or the hg38 assembly from UCSC, then all of your reference data will be using the same coordinate system along the basepairs of the chromosomes. This is important, since this tool suite is comparing coordinates in the
bamdata against thegtfdata to generate the results. - If the reference genome assembly was instead sourced from NCBI or Ensembl, then this is one place to double check for potential input problems that can lead to unexpected results. The guide here explains with more details. → Reference genomes at public Galaxy servers: GRCh38/hg38 example
- One extra tip – you could attach the CVMFS resource to your local Galaxy server. This would automatically link all the reference data we host at the public servers. May make things easier! See → Hands-on: Reference Data with CVMFS / Reference Data with CVMFS / Galaxy Server administration or Hands-on: Reference Data with CVMFS without Ansible / Reference Data with CVMFS without Ansible / Galaxy Server administration. You can still have customize reference data along side this!
- We can’t see which reference genome you used for the mapping step to create the
Other than that, different parameters can impact the results of course! The original manual from the tools and potentially online discussion at a scientific forum like Biostars.org are the resources to review to learn about fine tuning for specific outcomes. The tool will work in Galaxy about the same as anywhere else. Or, should. If you notice some bug with the tool wrapper, you can report this to the developer at their Github repository.
Xref
- GitHub - Xinglab/rmats-turbo
- Example discussion at the author Github about reference data, parameters, and how the tool is processing the data. If I am understanding correctly, they seem to think Gencode is a good annotation choice! → rMATS Reference Files – Clarification · Issue #521 · Xinglab/rmats-turbo · GitHub
So – I think the tool is working as expected! Please let us know if this helps or not. 