Fig. 4
From: Alevin efficiently estimates accurate gene abundances from dscRNA-seq data
a The Spearman correlation between quantification estimates (summed across all cells) from different scRNA-seq methods against bulk data from the mouse neuronal and human PBMC datasets, stratified by gene sequence uniqueness. The bar plot on the top of each figure shows the percentage of genes in each bin that have unique read evidence. Tier 1 is the set of genes with only uniquely mapping reads. Tier 2 is genes that have ambiguously mapping reads, but are connected to unique read evidence that can be used to resolve the multimapping reads. Tier 3 is genes that are completely ambiguous. Note that all methods perform very similarly on genes from tier 1, but the performance of alevin is much better for the other tiers. b Comparison of various methods used to process Drop-seq data from mouse retina with 4k cells. The Spearman correlation is calculated against bulk quantification estimates predicted using Bowtie2 and RSEM on data from the same cell type