4.9 years ago by
I have personally not been very impressed with the transcript-level qualifications, especially with RNA-Seq data with very uneven coverage (which is almost all the data I have directly worked with, although I've heard there are newer protocols to assist with the problem of uneven coverage). For this reason, I would tend to stick towards analyzing differential splicing events (exon skipping, intron retention, etc.) with MATS, MISO, etc. over whole transcript quantification (and I tend to use gene-level mRNA quantification rather than transcript-level mRNA quantification)
That said, you could take the transcript abundances from cufflinks, RSEM, etc. and treat them like a normal, gene-level differential expression experiment (using limma, sRAP, etc.). I don't think this a great solution, but I don't know if it is really much worse than using cuffdiff.
To get an idea about the robustness of gene-level vs. transcript-level differential expression would look like, you can see Figure 5 in the following paper (although it may not be a completely fair comparison because the gene-level and transcript-level expression will often be correlated, and discrepancies between transcript abundances shouldn't be expected for all genes):