in 2016, the field has expanded rapidly, with diverse platforms now spanning sequencing-based (e.g., Visium, Visium HD, Slide-seq, Stereo-seq, and Seq-Scope) and imaging-based (e.g., MERFISH, Xenium, and CosMx SMI) approaches. The breadth of platforms, data structures, and computational tools, however, can be daunting for newcomers.
by Nagomi Kurogi, Koki Shimbara, Tatsuya Koreeda, Koki Tsuyuzaki Spatial transcriptomics (ST) enables genome-wide gene expression profiling while retaining spatial context within tissue sections.
The breadth of platforms, data structures, and computational tools, however, can be daunting for newcomers.
We further discuss interpreting spatial patterns in biological context, integrating complementary modalities such as single-cell RNA sequencing and spatial proteomics, and leveraging public datasets and...
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by Nagomi Kurogi, Koki Shimbara, Tatsuya Koreeda, Koki Tsuyuzaki Spatial transcriptomics (ST) enables genome-wide gene expression profiling while retaining spatial context within tissue sections. in 2016, the field has expanded rapidly, with diverse platforms now spanning sequencing-based (e.g., Visium, Visium HD, Slide-seq, Stereo-seq, and Seq-Scope) and imaging-based (e.g., MERFISH, Xenium, and CosMx SMI) approaches. The breadth of platforms, data structures, and computational tools, however, can be daunting for newcomers.
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