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The central principle is to attach a recoverable spatial address to an RNA-derived molecule before the tissue's positional organization is destroyed. After sequencing, each read identifies both a transcript and a capture location.

In the original array-based spatial transcriptomics method, a thin tissue section is placed on a slide carrying spatially indexed capture primers. The tissue is imaged for histology, then permeabilized. Polyadenylated messenger RNA binds the oligo(dT) region of the primers and is copied by reverse transcription. The resulting cDNA carries the positional barcode. Sequencing identifies the expressed gene, and a barcode lookup places its counts back on the tissue image. The first published array used approximately $100\mu \mathrm{m}$ capture features, so a feature could contain contributions from several cells; it was not a single-cell measurement by construction.^[ref]

Slide-seq applies the same addressing idea using a dense monolayer of roughly $10\mu \mathrm{m}$ barcoded beads. The bead barcode–position map is decoded in advance. A tissue section is transferred onto the beads, released RNA is captured, and the sequenced molecular addresses recover the bead-level expression map. This gives much finer spatial sampling than the original coarse array, although RNA capture efficiency and assignment to individual cells remain limiting.^[ref]

Some assays also incorporate a unique molecular identifier so that amplified reads from one captured molecule can be collapsed, reducing polymerase chain reaction duplication bias. Spatial barcodes identify capture locations; unique molecular identifiers identify molecules within those locations. Neither alone supplies cell boundaries.

For either method, align the coordinate map with histology, account for capture efficiency and background, and use independent tissue specimens as biological replicates. A smaller capture feature improves sampling granularity but does not guarantee equal effective spatial resolution or a pure single-cell transcriptome: tissue thickness, diffusion and mixed cell boundaries still matter.

Teemu Kivioja led work on counting original nucleic-acid molecules using unique molecular identifiers. A sequence label attached before amplification lets descendants of one starting molecule be recognized, so repeated reads from that molecule need not be mistaken for many independent originals.^[ref]

For example, a hundred reads with one valid molecular identifier can represent one amplified starting molecule, whereas a hundred different valid identifiers can represent many originals. Identifier collisions and sequencing errors complicate that idealization. The contribution links molecular population measurement to an explicit observation model, separating amplification yield from original molecular abundance.

A unique molecular identifier is a short sequence tag attached so that observations derived from the same original molecule can be grouped. It helps distinguish amplification duplicates from independently captured templates. If two originals receive the same tag, a collision can merge them; sequence errors can instead split one tag into several apparent groups. The tag space, assignment method and error correction therefore limit molecule-count accuracy. ^[ref]