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Pros and cons


  • Commercial kit
  • Low cost
  • Single well capture with randomly primed and polyT oligos in the same library

Cons: * Fewer datasets available compared to other single cell technologies

Getting Started

The vignettes below provide examples of processing raw data using a workflow that includes seqspec, gget, and kallisto/bustools to generate a count matrix. We process the output of various transcriptomics technologies into a SpatialFeatureExperiment(SFE) object for use with Voyager.

Vignette Colab Notebook Description
Preprocess raw data Colab Notebook Fetch reference data with gget, process raw data with seqspec, generate a count matrix with kallisto-bustools
Create a SFE object Colab Notebook Download data, create SFE object

Analysis Workflows

The analysis tasks include basic quality control, spatial exploratory data analysis, identification of spatially variable genes, and computation of global and local spatial statistics. Accompanying Google Colab notebooks are linked.

Vignette Colab Notebook Description
SPLiT-seq Basic QC Colab Notebook Basic qc and preprocessing