Biostar Beta. Not for public use.
how can interpret these biologically weird results?
0
Entering edit mode
10 months ago
Mozart • 130

Hello there, as final results of my pipeline (sleuth) I obtained a redundancy in terms of different transcript related to the same gene, up and down regulated at the same time.

Any hints on how to interpret these results? I would expect at lest these transcript had the same 'direction'

   transcript                   qval         estimate std_error
   ENSMUST00000194462.5         0.23261738  4.9713734 0.1869298
   ENSMUST00000193838.1         0.03842443 -2.0165854 0.9536398
RNA-Seq • 599 views
ADD COMMENTlink
3
Entering edit mode

Come on, without any details on your experiment, your hypothesis, the conditions, what these transcripts are and why you think that this is a weird result, how can you expect anyone to help you?

ADD REPLYlink
0
Entering edit mode

Thanks for your reply, sorry for that but let me reformulate the question: at this point I am not asking help about the 'strings of code' I used; I have an experiment with 2 conditions (KO and WT mouse, these are the results from the KO mice). I mean let's assume what I have done so far is correct, alright? how would you interpret these results?

ADD REPLYlink
3
Entering edit mode

It is impossible to interpret without knowing the context.

ADD REPLYlink
0
Entering edit mode

thanks I have just put the parts required down below

ADD REPLYlink
1
Entering edit mode

Wolfgang Amadeus Mozart, I like your music, you should show more information like:

  • the base mean for each of these transcripts
  • the unadjusted P value
  • the sample number
  • missing values over each transcript
  • variance of each transcript

Look at each of those and you may get nearer to the truth.

ADD REPLYlink
1
Entering edit mode

I am not allowed to reply in 6 hours so I basically modified the post below!

ADD REPLYlink
1
Entering edit mode

Repost here. Maintain fluidity of the conversation. Also, you have not added anything that we had asked ... (?).

ADD REPLYlink
0
Entering edit mode
                 target_id           ens_gene ext_gene
38604 ENSMUST00000194462.5 ENSMUSG00000027737  Slc7a11
38492 ENSMUST00000193838.1 ENSMUSG00000027737  Slc7a11
3477  ENSMUST00000029297.5 ENSMUSG00000027737  Slc7a11
25123 ENSMUST00000142932.2 ENSMUSG00000027737  Slc7a11
ADD REPLYlink
4
Entering edit mode

Thanks for reposting here. It's just what I had expected was happening here.

Look at the var_obs column. The variance for ENSMUST00000194462.5 is completely inflated, ~8-9 times greater than the others. This will result in unreliable fold-changes and P values.

rss and tech_var neither look so hot.

ATPoint, what do you think?

ADD REPLYlink
0
Entering edit mode

Sorry but if I am not mistaking this means that when you filter your result the most significant (statistically and by fold change) is the only one I should consider?

ADD REPLYlink
1
Entering edit mode

Yes of course. The general rule is:

  • absolute log2 fold change >2

and

  • FDR Q value (adjusted P value) ≤0.05

The high variance of the transcript resulted in it not passing FDR adjustment, highlight just how important these adjustments are.

ADD REPLYlink
0
Entering edit mode

Thanks a lot...and sorry if sometimes I am not that precise.

ADD REPLYlink
1
Entering edit mode

Absolutely no problem my friend. If you are indeed the real Mozart, then keep up the great music!

ADD REPLYlink
0
Entering edit mode

I will do my best!!! ahahah

ADD REPLYlink

Login before adding your answer.

Similar Posts
Loading Similar Posts
Powered by the version 2.1