On 2013 Nov 01, Stephen Turner commented:

RNA-seq enables transcript-level resolution of gene expression, but there is no appropriate methodology for simultaneously accounting for biological variability across replicates and uncertainty in mapping fragments to isoforms. Figure 1 in this paper illustrates the problem with existing approaches, which only count the number of fragments originating from either the entire gene or constitutive exons only. The method presented here addresses both of these problems simultaneously by modeling variability in the number of fragments generated by each transcript across biological replicates. Compared to existing methods, the procedure described here has equivalent sensitivity with a much lower false-positive rate when there is substantial isoform-level variability in gene expression between conditions. The manuscript also addresses and points out weaknesses in several undocumented 'alternative' workflows that are highly discussed in the field, where transcript counts from tools like Cufflinks and RSEM (RNA-Seq by expectation maximization) are used in downstream negative-binomial-based differential expression analyses.

On 2013 Nov 01, Stephen Turner commented:

RNA-seq enables transcript-level resolution of gene expression, but there is no appropriate methodology for simultaneously accounting for biological variability across replicates and uncertainty in mapping fragments to isoforms. Figure 1 in this paper illustrates the problem with existing approaches, which only count the number of fragments originating from either the entire gene or constitutive exons only. The method presented here addresses both of these problems simultaneously by modeling variability in the number of fragments generated by each transcript across biological replicates. Compared to existing methods, the procedure described here has equivalent sensitivity with a much lower false-positive rate when there is substantial isoform-level variability in gene expression between conditions. The manuscript also addresses and points out weaknesses in several undocumented 'alternative' workflows that are highly discussed in the field, where transcript counts from tools like Cufflinks and RSEM (RNA-Seq by expectation maximization) are used in downstream negative-binomial-based differential expression analyses.