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.
Explore Datasets
Interact with Parse computational pipeline outputs from three separate single cell sequencing datasets below. All interactive output files are viewable on any standard browser, without any software downloads. These reports illustrate the unparalleled quality and sensitivity of data obtainable with the Parse Whole Transcriptome Kits, in both transcript and gene detection for samples as large as 100,000 cells.
To download any of the following datasets, click on the “Explore Dataset” button below. You will have the option to download an interactive html experimental report, a digital gene matrix, a spreadsheet of cell metadata, and a comprehensive list of genes.
High Resolution Profiling of Immune Cells
PBMCs from a Healthy Donor – 67,000 cells
- Explore how the Parse Whole Transcriptome Kit enables sensitive single cell profiling across all immune cell types and sub-types.
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View how the Whole Transcriptome Kit enables robust detection of genes such as CD4 and CD8 that are often missed in single-cell RNA-sequencing
Profiling Single Nuclei from an Embryonic Mouse Brain
E18 Mouse Whole Brain – 62,000 Nuclei
- Explore how the Parse Whole Transcriptome Kit maintains high transcript and gene detection in nuclei (15,000 and 3,700/nuclei respectively).
- See the specificity of cluster-specific genes expression (up to 4000x enrichment), with much lower levels of background contamination than other single cell sequencing solutions.