This paper by Soneson, Love, and Robinson discusses the advantages of gene-level abundance estimates over transcript-level analyses in RNA-seq data analysis. The authors argue that gene-level estimates are more accurate, robust, and interpretable, particularly in the context of differential gene expression (DGE) studies. They demonstrate that incorporating transcript-level abundance estimates into count-based statistical inference methods can improve the performance of DGE analyses, especially for genes with differential isoform usage. The study uses simulated and real data sets to compare various quantification approaches, including simple read counting and transcript-level estimation methods like Salmon. The authors also introduce the R/Bioconductor package `tximport`, which facilitates the integration of transcript-level abundance estimates into statistical inference engines. The paper highlights the importance of carefully specifying the biological question when selecting an analysis approach and provides a comprehensive evaluation of different methods for transcript and gene-level analyses.This paper by Soneson, Love, and Robinson discusses the advantages of gene-level abundance estimates over transcript-level analyses in RNA-seq data analysis. The authors argue that gene-level estimates are more accurate, robust, and interpretable, particularly in the context of differential gene expression (DGE) studies. They demonstrate that incorporating transcript-level abundance estimates into count-based statistical inference methods can improve the performance of DGE analyses, especially for genes with differential isoform usage. The study uses simulated and real data sets to compare various quantification approaches, including simple read counting and transcript-level estimation methods like Salmon. The authors also introduce the R/Bioconductor package `tximport`, which facilitates the integration of transcript-level abundance estimates into statistical inference engines. The paper highlights the importance of carefully specifying the biological question when selecting an analysis approach and provides a comprehensive evaluation of different methods for transcript and gene-level analyses.