10X Chromium Single Cell 3’ v3 Processing Workflows with Voyager

The 10X Genomics Chromium Single Cell 3’ v3 solution is a droplet-based single cell sequencing technology that enables gene expression profiling in hundreds to tens of thousands of cells. In a typical protocol, cells are dissociated and captured in Gel Beads-in-emulsion (GEMs). All cDNA from a single cell share a cellular barcode. Additional 10X barcodes help associate individual reads from a cDNA library back to the originating GEMs. The gel beads in the v3 chemistry are also modified to enable feature barcoding, so that orthogonal molecules can be profiled alongside RNA. This, in addition to greater detection of RNA molecules, represents major advancements over the 10X Chromium v2 chemistry.

Pros and cons

Pros:

• Widely used, tested on many cell types and tissues
• Many existing datasets, including many on the 10X website
• High throughput, applied to atlases with millions of cells

Cons:

• Lose spatial information
• More expensive than open source technologies
• Less flexible
• Some tissues such as skeletal muscles are challenging to dissociate

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

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 Colab notebooks are linked.

Vignette	Colab Notebook	Description
10X v3 Basic	Colab Notebook	Standard analyses for non-spatial scRNA-seq data
ClickTag Basic QC	Colab Notebook	Standard QC for scRNA-seq data