Reference

All functions
StatModel()	StatModel
Tasic_counts_vignette	A `Matrix` with transcript-level counts derived from our case study which builds on the dataset of Tasic et al. We used Salmon (V1.1.0) to quantify all L5IT cells (both for ALM and VISp tissue) from mice with a normal eye condition. From these cells, we randomly sampled 20 cells of each of the following cell types to use for this vignette; L5_IT_VISp_Hsd11b1_Endou, L5_IT_ALM_Tmem163_Dmrtb1 and L5_IT_ALM_Tnc. The data has already been leniently filtered with the `filterByExpr` function of edgeR. After this, the transcripts of the first 3000 genes were retained to further reduce the size of the data object.
Tasic_metadata_vignette	Metadata associated with the expression matrix `Tasic_counts_vignette`. See `?Tasic_counts_vignette` for more information on the dataset.
fitDTU()	fitDTU
plotDTU()	Plot function to visualize differential transcript usage (DTU)
StatModel-class .StatModel	The StatModel class for satuRn
getModel(<StatModel>) getDF(<StatModel>) getDfPosterior(<StatModel>) getDispersion(<StatModel>) getCoef(<StatModel>)	Accessor functions for StatModel class
sumExp_example	A `SummarizedExperiment` derived from our case study which builds on the dataset of Tasic et al. It contains the same cells as the data object used in the vignette (see `?Tasic_counts_vignette` for more information). In this SummarizedExperiment, we performed a filtering with `filterByExpr` of edgeR with more stringent than default parameter settings (min.count = 100,min.total.count = 200, large.n = 50, min.prop = 0.9) to reduced the number of retained transcripts. We used this object to create an executable example in the help files of satuRn.
testDTU()	Test function to obtain a top list of transcripts that are differentially used in the contrast of interest