Contrary to some assumptions in the field, several concepts about spatial omics are misunderstood. These misconceptions can influence experimental design and technology selection. This article clarifies three common areas of confusion, providing a clearer view of modern spatial transcriptomics and integrated multi-omic approaches. The platform from STOmics exemplifies how contemporary tools address these very points.
Myth 1: Resolution and Throughput Are Always a Trade-Off
A prevailing idea is that high-resolution spatial transcriptomics requires sacrificing the analysis of large tissue areas. This is no longer a universal constraint. Advanced technologies, such as the Stereo-seq platform from STOmics, demonstrate that subcellular resolution and centimeter-scale field-of-view analysis can be achieved simultaneously. This capability allows researchers to study intricate cellular neighborhoods without losing sight of the broader tissue architecture.
Myth 2: Proteins and Transcripts Must Be Studied Separately
Many studies treat protein and gene expression data as separate entities, correlating them after separate experiments. Integrated spatial omics challenges this sequential approach. A complete spatial omics platform enables the co-profiling of the transcriptome and proteome from the same tissue section. This simultaneous measurement provides a more direct and precise understanding of molecular relationships within their native spatial context.
Myth 3: Data Analysis Is an Insurmountable Bottleneck
The complexity of spatial transcriptomics data can seem daunting. The perception that analysis requires exclusively in-house, custom-built bioinformatics pipelines can delay projects. However, end-to-end solutions now include robust, standardized analysis software. These integrated bioinformatics tools are designed to transform raw, spatially resolved data into actionable biological insights, streamlining the workflow from imaging to interpretation.
Dispelling these myths allows research teams to better leverage the power of spatial biology. Acknowledging that resolution and scale can coexist, that multi-omic integration is feasible, and that analysis pipelines are accessible changes how scientists approach their spatial study designs. Platforms like the one offered by STOmics are built to meet these very capabilities, supporting researchers in moving beyond limitations.
