Hi,
I am new to use rMATS for alternative splicing detection. I have a few questions:
i noticed that the default is no detection of novel splice sites (-novelSS 0). Why are there still files like 'fromGTF.novelEvents.A3SS.txt' in the ASEvents folder?
AS_Event.MATS.JunctionCountOnly and AS_Event.MATS.ReadsOnTargetAndJunctionCounts generated different results. What are the advantages and disadvantages for these two types of files?
Thanks in advance.
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zhaopeihua0520 •
I see that you haven't gotten a response yet for your most in the rMATS discussion group:
https://groups.google.com/forum/#!topic/rmats-user-group/s8-VOy4HFJM
MATS provides splicing events defined from a number of different resources. According to this post, rMATS can define some types of novel junctions:
Ideally, I would say being able to incorporate additional information would be better for making more accurate predictions. However, if I remember correctly, you'll tend to get more events called from "JunctionCountOnly".
If you have replicates and are willing to try other programs, I like JunctionSeq (basically an extension of DEXSeq) a little better. It only discovers novel junctions between known exons, but I think that is similar to rMATs. It also doesn't provide specific annotations (just differences in coverage for exons and junctions), but I would say it does a decent job of identifying genes with some sort of splicing change and it provides a nice visualization for those differences across your replicates.
Thanks for your help.
I am trying to use JunctionSeq. But i don't understand why JunctionSeq tests for differential usage of both exons and splice junctions simultaniously. I think that differential exon usage also means differential splce junction usage.
1) If the splice junction has a change in coverage for corresponding exon(s), that provides additional evidence that the splicing event is real (and vice versa).
2) If there is differential splicing with a novel exon, you would see a change in splicing junction coverage that might not show a clear change among known exons.
If you want to find potential novel exons associated with difference in junction coverage, you would try a program like SGSeq (although I haven't had a chance to do very careful testing of that program):
https://bioconductor.org/packages/release/bioc/html/SGSeq.html
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