  Mapping spatial distributions of transcriptomic cell types is essential to
understanding the brain, with its exceptional cellular heterogeneity and the
functional significance of its spatial organization. Spatial transcriptomics
techniques are hoped to accomplish these measurements, but each method uses
different experimental and computational protocols, with different trade-offs
and optimizations. In 2017, the SpaceTx Consortium was formed to compare these
methods and determine their suitability for large-scale spatial transcriptomic
atlases. SpaceTx work included progress in tissue processing, taxonomy
development, gene selection, image processing and data standardization, cell
segmentation, cell type assignments, and visualization. Although the landscape
of experimental methods has changed dramatically since the beginning of
SpaceTx, the need for quantitative and detailed benchmarking of spatial
transcriptomics methods in the brain is still unmet. Here, we summarize the
work of SpaceTx and highlight outstanding challenges as spatial transcriptomics
grows into a mature field. We also discuss how our progress provides a roadmap
for benchmarking spatial transcriptomics methods in the future. Data and
analyses from this consortium, along with code and methods are publicly
available at https://spacetx.github.io/.
