Welcome, @Hossein_Poursheykhi
Thanks for explaining what is going wrong. There are two potential things going on when a count result is unexpected.
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This is an actual scientific result.
Counts could be zero for some or all features if the reads did not map to the same genomic places (species, then assembly’s chromosomes and coordinates) as the features you are counting up.
So, make sure the reference data and sequencing targets are synched up! By this I mean: do you expect those reads to map to those features? Have you looked at the BAM and GTF in a genome browser to see if that reveals anything? If you do this at a site like UCSC, you can also toggle on other annotation tracks to help clarify what you might be observing.
Or, reads can multi-map to so many places that the counting tool discards the hits for being non-specific. Ironically, this can be due to trying to save reads that should be rejected during QA. Meaning: fewer high quality reads can be more informative than a zillion low quality reads.
An experiment will usually have a combination of all these going on – and a “good” experiment has “most” reads that map uniquely to the genomic regions of interest.
Good sequencing library design, good reference data, good technical execution == good scientific results!
Maybe your annotation features really do not have any coverage from the sequenced library, and that can be explored for both scientific insights and potential ways to adjust techniques for next time.
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This is a poor scientific result.
The problem could be with any of these parts:
Good sequencing library design, good reference data, good technical execution
If the job is failing, not just producing a poor result, that is also a bit informative since the tool is probably providing some details about what it guesses is going wrong. Not always correct but those are usually useful hints about where to start!
We can help with decoding those messages at this forum, plus explain the things to check for if the results are just “odd” and not actually failing.
We have tutorials with examples. Find these at the main site or review the bottom of tool forms for mini examples and links into those full length tutorials. You can also explore our FAQs, and this forum.
- All → https://training.galaxyproject.org/
- RNA-Star → Galaxy Training!
- FAQ → FAQ: Extended Help for Differential Expression Analysis Tools
My guess is that there is some mismatch with the reference data. If you would like help with this, you can share back your work for feedback. Generate the share link to your history with the problem results and the inputs, and post that back here. You can unshare after.
Let us know if you are able to solve this, and I’ll watch for your reply if you choose to share your history! Thanks!