Fig. 2

a This figure illustrates examples of various classes of UMI collisions and which method(s) would be able to correctly resolve the origin of the multimapping reads in each scenario. These cases are shown top to bottom in order of their likelihood. b A simulated example demonstrates how treating equivalence classes individually during UMI deduplication can lead to under-collapsing of UMIs compared to gene-level methods (especially in protocols where the majority of cDNA amplification occurs prior to fragmentation). In the first row, both methods report correctly two UMIs. In the second row, there are two fragmented molecules aligned against two transcripts from the same gene. The alevin deduplication algorithm will attempt to choose the minimum number of transcripts required to explain the read mappings and hence correctly detect the UMI counts. The equivalence class method will over-estimate the gene count