Figure 6:

Spacemake offers several processing modes while producing a unified downstream output and can align spatial count data with H&E images. (A) Spacemake can be run using several user-defined settings. Gene quantification depends on the run-mode set to include reads mapping only on exons, on both exons and introns, on exons and intergenic regions, and whether the reads should be trimmed for poly(A)-tails and adapters. (B) Comparison of spacemake run-modes with spaceranger. Genes with twice higher counts are colored red (higher in spaceranger) or green (higher in spacemake); all other genes are colored gray. (C) Spacemake automatically performs clustering analysis of the data. At 1.2 resolution, clusters become distinct along defined structures in space, such as the cortical layers, CA2/CA3, CA1, and dentate gyrus. (D) Spacemake automatically aligns spatial transcriptomics data with H&E images. Here the pyramidal layers and the dentate gyrus, as taken from the Allen Brain Atlas, are shown to perfectly overlap with the corresponding clusters.