Extended Data Fig. 6: Overview of permutation score construction.

a. First, the cells of one cell type are selected. These are shuffled independently for each genes (and independently in each of unspliced and spliced matrices). This is repeated for each cell type and the data are concatenated. This new permuted dataset is fed into a pre-trained veloVI model (trained on the same original dataset). The fit of unspliced and spliced abundance is obtained for each new perturbed cell. Following this, for each gene, the mean absolute error (spliced and unspliced) is computed per cell type. The original and perturbed mean absolute errors are compared with the T-test statistic. This provides a permutation effect statistic for each gene and each cell type. To obtain the permutation score, a scalar score for each gene, we take the maximum permutation effect statistic across cell types.