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how can interpret these biologically weird results?

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?

rna-seq
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updated by Biostar Biostar • written by Mozart Mozart

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?

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written by ATpoint ATpoint

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?

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written by Mozart Mozart

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.

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written by Kevin Blighe Kevin Blighe

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

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written by Mozart Mozart

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

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written by Kevin Blighe Kevin Blighe

It is impossible to interpret without knowing the context.

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written by ATpoint ATpoint

thanks I have just put the parts required down below

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written by Mozart Mozart 
                 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
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written by Mozart Mozart

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?

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written by Kevin Blighe Kevin Blighe

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?

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written by Mozart Mozart

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.

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written by Kevin Blighe Kevin Blighe

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

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written by Mozart Mozart

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

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written by Kevin Blighe Kevin Blighe

I will do my best!!! ahahah

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written by Mozart Mozart

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