This dataset contains results from paired differential expression and differential splicing analyses as well as gene-set over-representation analysis results for 199 baseline vs. case comparisons across 100 randomly curated datasets with accompanying metadata (preprint). All results were computed using the R package pairedGSEA, which utilized DESeq2 (Love et al., 2014), DEXSeq (Anders et al., 2012), and fgsea (Korotkevich et al., 2019). See limma results here: https://doi.org/10.5281/zenodo.7866420 Each .RDS file contains a list with three objects: A 'metadata' object with the metadata of the respective raw data, a 'genes' object with gene-level differential splicing and expression results, and a 'gene_set' object with over-representation results. The filenames follow this pattern: "[dataset ID]_[GEO accession number]_[Manually assigned comparison title].RDS". All datasets were obtained from a local copy of the ARCHS4 v11 database of transcript counts (Lachmann et al., 2018).

{"references": ["Lachmann, A., Torre, D., Keenan, A.B. et al. Massive mining of publicly available RNA-seq data from human and mouse. Nat Commun 9, 1366 (2018). https://doi.org/10.1038/s41467-018-03751-6", "Love, M.I., Huber, W., Anders, S. Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2 Genome Biology 15(12):550 (2014)", "Anders, S., Reyes, A., & Huber, W. (2012). Detecting differential usage of exons from RNA-seq data. Genome Research, 22(10), 2008\u20132017. https://doi.org/10.1101/gr.133744.111", "G. Korotkevich, V. Sukhov, A. Sergushichev. Fast gene set enrichment analysis. bioRxiv (2019), doi:10.1101/060012"]}