Quantification and equivalence classes

The project contains the quantification output of Salmon (including equivalence classes) from simulated RNA-seq data for 12 paired-ended samples (i.e., biological replicates).Reads were first aligned via splice-aware genome aligner STAR, then Salmon was used on the aligned reads to compute transcript-level estimated counts (quant.sf files) and equivalence classes (aux_info/eq_classes.txt files).100 bootstrap replicates are computed from Salmon for each sample.Samples belong to two groups: samples 1 to 6 constitute the first group, while samples 7 to 12 represent the second group.In each group 1,000 genes exhibit differential transcript usage (DTU) and further 1,000 genes (partially overlapping with the previous set) shows differential gene expression (DGE) between groups.Genes showing DTU were simulated by randomly permuting the relative abundance of the four most expressed transcripts; for gene with two or three transcripts only, all transcripts relative abundances were permuted.The dataset is used to benchmark DTU methods in the manuscript entitled "BANDITS: Bayesian differential splicing accounting for sample-to-sample variability and mapping uncertainty".The code for simulating the data is available on GitHub at https://github.com/SimoneTiberi/BANDITS_manuscript .