Learning Outcomes

• Understand the basics of running the Cellranger Count Pipeline in Foundry.

Cellranger Count Pipeline Run Tutorial

Attaching Data to Foundry

1. From the Data tab, click the URL section. Enter the URL:

   https://www.viafoundry.com/test_data/fastq_10x_pbmc_1k_v3/
   

   and click Connect.

   

2. Select all files by checking the Select all box and click Continue with Selected Files.

   

3. In the Dataset Type dropdown, select Paired List. While holding Shift, select both entries and click Merge Selected Files.

   

4. Give the data collection a name (this name will be used for future runs) and click Save Files to Dataset. (Optional: You can edit the Name column to override the sample name.)

   

Submitting a Run

1. From the Pipelines tab, search for Cellranger Count Pipeline and click on the corresponding card.

   

2. On the Cellranger Count Pipeline page, click Run and select Create New Run.

   

3. Select a project (or create a new one), provide a run name, and click Create.

   

4. On the Run page, select your environment in the Run Environment section.

   

5. In the Inputs section, next to Reads, click the Upload File button.

   

6. In the Change Input File window, search for your dataset (using the previously assigned collection name) in the Filter By Dataset box. Check the box to add all files and click Save.

   

7. In the Inputs section, set mate to pair and genome_build to human_hg38_gencode_v32_cellranger_v6.

   

8. Leave the other inputs set to their default values.

9. Click Run in the top right, then select Start. The Cellranger Count Pipeline typically takes about one hour to complete.

10. Navigate to the Log tab and click on log.txt to follow the progress of your run.

    

Viewing Results

Count Web Summary

The output file in this section is an HTML file generated by the Cellranger Pipeline. This HTML file acts as a quality control report of the single-cell RNA-Seq Count Matrix and includes estimates of the number of cells, alignment and quantification results, as well as preliminary clustering analysis.

This report also includes a preliminary clustering analysis of the data. The preliminary results can serve as a means of quality control by indicating potential cell populations and their gene markers; however, these findings may not be fully accurate.

QC Plots

In the QC_Reports directory, you will find distributions of various properties both before and after cell filtering, including metrics such as the:

• Number of genes represented per cell
• Number of transcripts detected per cell
• Percent mitochondrial reads
• Percent ribosomal reads
• Doublet detection.

Final Report

The Final_Report directory contains summaries and visualizations of PCA, dimensionality reduction, clustering, and identified marker genes.

H5AD File

Within the H5AD_file directory, users can access and download the processed H5AD file and initiate the CellXGene app.

RDS File

In the scViewer directory, users can access and download the processed .RDS file and launch Foundry's scViewer app.