trouble with goseq

Hi there,
I am repeating the first part of “RNA-seq genes to pathways” tutorial using own data and cannot run Gene Ontology testing with goseq properly:
I am getting this awful GO plot. Here is a link to my history in case someone can check and give me some advise: Galaxy

NOTE: differntial gene expression (limma-voom) looked good

Hi @jpjviro

You have two problems going on.

  1. This prior topic described the first → Goseq NA NA NA NA values - #13 by jennaj

  2. And I suspect that missing database is also influencing why all of the genes are equally “ranked” in the output.

So, you’ll either need to create that database or check to see if someone has created it then run in an R environment. Cow is a model organism, so I would definitely check, and maybe ask here https://support.bioconductor.org/ to see if anyone knows.

On the Galaxy side, we already have a ticket about this, but it isn’t an algorithm fix, instead that is just to remove the options not actually supported by GOSEQ itself from even being possible on our tool form.

Back you your graph → Try outputting all of the optional files and inspect the over/under p-values. Notice that each result line has exactly the same p-values, so all qualify for the “top ten”, and you end up with everything in that graph.

Hope this helps! :scientist:

Update: Hum, I can’t find that other ticket, so I just created a new one. The developers can consolidate as needed. But for reference, please see or follow here → Goseq with custom gene-go-category term inputs = bad scientific outputs · Issue #6500 · galaxyproject/tools-iuc · GitHub

Hi @jennaj
I will go back to that history and check what you have highlighted! thanks!
That will help to track my error, comparing side by side with my new analysis…
On the good side, I repeated the analysis from scratch and worked this time

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Hey, wow, with the custom reference data? I would be interested in seeing how that works since I haven’t seen it work in a very long time, maybe never. Could you share a copy back? I like to learn, too. And I’m curious if the genes were promoted to that optional output (guessing not, but at least the graph works!). I can update the IUC ticket too once I know what exactly is missing versus possible. Thanks! :slight_smile:

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link to history above