I was going through the workflow "Swimming downstream: statistical analysis of differential transcript usage following Salmon quantification" which can be found here, https://f1000research.com/articles/7-952/v3#f4 and I wanted to clarify something.

Under the section DTE evaluation there is a sentence that says "For this assessment, all of the simulated non-null transcripts count as true positives of differential transcript expression, whether they originate from the simulated “DGE”, “DTE”, or “DTU” genes. For most of the methods, we simply provided the transcript-level data to the same functions as for the DGE analysis."

As mentioned there are investigators that prefer to assess DE on a per-transcript basis, does this mean one could use DGE methods at the transcript level?Is DTE in essence capturing any transcript that is DE, regardless of that status of that transcript (i.e. how many transcripts are expressed, and if the total gene-level does not change)?

Thanks!

hi,

We showed in that paper that the DGE methods can in practice be applied to transcript level quantification, and that some of the DGE methods perform reasonable well at transcript level on that simulated dataset which had various types of DTE spiked in, and realistic technical biases on the coverage. You can read off the performance at various sample sizes. As we say, I find that looking at DGE and DTU to be more interpretable about the changes in transcription (e.g. the DTU vs. DGE scatterplots we have in the workflow and paper), but I think it depends on the experiment and the biological question of interest which approach you might take. For the DTE analysis you are getting a p-value for DE of each transcript.