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How to create a Cell Ranger compatible V(D)J reference?
Question: I want to run Cell Ranger's V(D)J pipeline on an organism different from human or mouse. How can I create a compatible V(D)J reference?
Answer: To generate a Cell Ranger compatible reference for the V(D)J pipeline using the Ensembl database, you will need the reference genome FASTA and its corresponding gene annotations in GTF format for your organism. Then, you can run the Cell Ranger's cellranger mkvdjref utility to generate a compatible reference package.
To generate your reference using the IMGT database, use the fetch-imgt script provided with Cell Ranger v2.1+ to fetch the data from IMGT. Then run cellranger mkvdjrefto generate the reference.
Click here for more details on building a Cell Ranger compatible reference for the V(D)J pipeline. Also see a related KB article on building a custom reference for V(D)J using IMGT tool.
Note: Currently, in Cloud platform we do not support running Cell Ranger V(D)J in de novo mode without a reference. We are planning to add support for this option in Cloud in a future release. De novo mode without a reference is enabled in cellranger command line.
Related Article: Usage of Cell Ranger VDJ denovo mode
Product: Single Cell Immune Profiling
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Can I use Cell Ranger to analyze cell hashing data?
Question: I have single-cell gene expression samples prepared with a cell hashing protocol. Can I use Cell Ranger to analyze these data?
Answer: 10x Genomics now supports Feature Barcoding technology for Cell Multiplexing (CellPlex). This technology utilizes species-agnostic, lipid-based tagging compatible with cells or nuclei to load up to 12 samples onto one GEM well. Please see this page for more information. We also provide the cellranger multi pipeline in Cell Ranger (6.0 or later) to analyze 10x Genomics Cell Multiplexing data.
If you have used custom antibody-based hashtag oligos (HTOs) for sample multiplexing, you may use the cellranger multi pipeline in Cell Ranger v6+ by providing a reference for custom multiplexing oligos. However, because the data generated from a custom workflow for multiplexing (e.g. CITE-seq) has not been validated with Cell Ranger’s algorithms, we cannot support custom workflows for multiplexing. Cell Ranger multi-web summaries will also provide a warning to customers to let them know a custom multiplexing reagent has been detected. Users should exercise caution when interpreting results generated with custom reagents.
If you encounter issues generating HTO libraries or any other custom reagents, we recommend contacting the vendor (e.g. New York Genome Center or BioLegend) directly.
Related articles:
How to analyze 5' multiplexed GEX+VDJ+FB(custom) data on multiple samples
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How do I get the read counts for each barcode?
Question: Is there a way to get the read counts for each barcode in addition to UMIs?
Answer: Most customers only want the UMI counts because it corrects for amplification bias. If you are interested in the read counts, then you can extract them from the possorted_genome_bam.bam file with some custom coding. The Linux command shown below requires samtools, a copy of which can be found in your Cell Ranger installation.
Before starting, you should source the following file so Linux knows where to find samtools. Please be sure to change the bolded part below based on the location of the Cell Ranger version you have installed:
source /path/to/cellranger-x.y.z/sourceme.bash
Afterwards, the following command will compute reads per barcode. Try it out with the first 1000 reads to see if the output matches expectation. If the test run checks out, then you can remove the bolded | head -n 1000 to process the entire bam file.
samtools view possorted_genome_bam.bam | head -n 1000 | grep CB:Z: | sed 's/.*CB:Z:\([ACGT]*\).*/\1/' | sort | uniq -c > reads_per_barcode
Please keep in mind that this command can take a while to run since the computer needs to stream through the entire BAM file, and sort millions of barcodes.
Disclaimer: This article and code-snippet are provided for instructional purposes only. 10x Genomics does not support or guarantee the code.