The Parse Biosciences Single Cell Whole Transcriptome Kit
The Whole Transcriptome Kit enables you to easily increase the number of samples and cells in your single cell experiment. The workflow makes it possible to:
✓ Profile anywhere from 1 to 48 samples per experiment across 100,000 cells
✓ Run fixed samples collected on different dates together in a single experiment
✓ Perform the whole workflow with no custom instruments required
Furthermore, dramatic increases in transcript detection from the original SPLiT-seq method allow you to capture more information with less sequencing while avoiding doublets.
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Parse Biosciences Workflow
Lock in gene expression immediately after tissue dissociation with a rapid fixation protocol. After fixation your samples can be stored for up to 6 months or you can proceed directly to barcoding.
Starting with 1-48 fixed biological samples, pass cells through three split-pool combinatorial barcoding steps to append a cell-specific combination of DNA barcodes to each transcript.
Prepare barcoded molecules for next generation sequencing. Up to 8 sequencing sublibraries (each containing 100-12,500 cells) can be prepared in parallel. Sublibraries can be sequenced independently at different sequencing depths.
After sequencing, use our computational pipeline to generate an experimental report along with processed data (including gene-cell count matrix) that integrates into existing open source tools (Seurat, Scanpy, etc.)
Parse Biosciences Software
The Parse Biosciences computational pipeline is an out-of-the-box software tool that you can run locally to convert fastq files straight to processed data (including gene-cell count matrices). Customers purchasing the Whole Transcriptome Kit will receive access to the Parse computational pipeline.
Summary statistics provide information necessary to diagnose sequencing runs. Interactive plots include a cell cutoff graph, sequencing saturation curves, and visual summaries of transcript and cell distribution across wells during barcoding. Statistics for each cluster marker are summarized in the differential expression table along with links to the NCBI database, and the interactive UMAP makes it possible to quickly interrogate genes of interest.