10x Genomics
Chromium Single Cell Gene Expression

Cell Ranger6.1, printed on 12/25/2024

Cell Multiplexing with cellranger multi

Cell Ranger 6.0 and later supports analyzing 3' Cell Multiplexing data with the cellranger multi pipeline.

Table of Contents

• When to use the multi pipeline
• Run cellranger mkfastq
• Run cellranger multi
• Example multi config CSVs
• CMO Reference

When to use the multi pipeline

The cellranger multi pipeline is required to analyze 3' Cell Multiplexing data. Otherwise, users can continue to use cellranger count.

Run cellranger mkfastq

First, follow the instructions on running cellranger mkfastq to generate FASTQ files. For example, if the flow cell ID was HAWT7ADXX, then cellranger mkfastq will output FASTQ files in HAWT7ADXX/outs/fastq_path. If you are already starting with FASTQ files, you can skip this step and proceed directly to run cellranger multi.

Run cellranger multi

Running cellranger multi requires a config CSV, described below, invoking the following arguments:

The multi config CSV contains both the library definitions and experimental design variables. It is composed of up to four sections for 3' data: [gene-expression], [libraries], [feature], and [samples]. Example formats for different product configurations are below.

The [gene-expression] and [feature] sections have at most two columns (Field name and value), and are responsible for configuring their respective portions of the experiment. The [libraries] section specifies where input FASTQ files may be found and has at least three columns. The [samples] section specifies sample information for Cell Multiplexing and has at least two columns.

A template for a multi config CSV can be downloaded here and example multi config CSVs can be downloaded from 6.0 public datasets here.

• After determining these input arguments, run cellranger multi (replace code in red with relevant file path and ID name):

cd /home/jdoe/runs
cellranger multi --id=sample345 --csv=/home/jdoe/sample345.csv

• Following a series of checks to validate input arguments, cellranger multi pipeline stages will begin to run:

Martian Runtime - v4.0.6
 
Running preflight checks (please wait)...
...

By default, cellranger will use all of the cores available on your system to execute pipeline stages. You can specify a different number of cores to use with the --localcores option; for example, --localcores=16 will limit cellranger to using up to sixteen cores at once. Similarly, --localmem will restrict the amount of memory (in GB) used by cellranger.

The pipeline will create a new folder named with the run ID you specified using the --id argument (e.g. /home/jdoe/runs/sample345) for its output. If this folder already exists, cellranger will assume it is an existing pipestance and attempt to resume running it.

• A successful cellranger multi run should conclude with a message similar to this:

Waiting 6 seconds for UI to do final refresh.
Pipestance completed successfully!
 
yyyy-mm-dd hh:mm:ss Shutting down.
Saving pipestance info to "tiny/tiny.mri.tgz"

• The outputs of the pipeline will be contained in a folder named with the run ID you specified (e.g. sample345). The subfolder named outs will contain the main pipeline outputs.

Example multi config CSVs

Here are a few example multi config CSVs for some common product configurations, along with simplified diagrams for the corresponding experimental set up. Make sure to replace /path/to with the actual full path to your data, and edit any text in red according to the experiment's sample/library/file names. The expect-cells option is recommended; up to 30,000 cells are supported for Cell Multiplexing.

• 3' Gene Expression with Cell Multiplexing, 1 CMO per sample
• 3' Gene Expression with Cell Multiplexing, multiple CMOs per sample
• 3' Gene Expression with Cell Multiplexing and Feature Barcode

Experimental Design	Multi config CSV
3' GEX with Cell Multiplexing, 1 CMO/sample See example dataset	[gene-expression] reference,/path/to/transcriptome expect-cells, enter expected number of recovered cells include-introns,true [libraries] fastq_id,fastqs,feature_types gex1,/path/to/fastqs,Gene Expression mux1,/path/to/fastqs,Multiplexing Capture [samples] sample_id,cmo_ids sample1,CMO301 sample2,CMO303
3' GEX with Cell Multiplexing, multiple CMOs/sample See example dataset. Note usage of the | to separate CMO tags. Learn more about when to use multiple CMOs per sample here.	[gene-expression] reference,/path/to/transcriptome expect-cells, enter expected number of recovered cells include-introns,true [libraries] fastq_id,fastqs,feature_types gex1,/path/to/fastqs,Gene Expression mux1,/path/to/fastqs,Multiplexing Capture [samples] sample_id,cmo_ids sample1,CMO301|CMO302 sample2,CMO303|CMO304
3' GEX with Cell Multiplexing and Feature Barcode The Feature Barcode in this config CSV example ([libraries] section) is Antibody Capture. Use CRISPR Guide Capture for CRISPR Feature Barcode experiments.	[gene-expression] reference,/path/to/transcriptome expect-cells, enter expected number of recovered cells include-introns,true [feature] reference,/path/to/feature_reference.csv [libraries] fastq_id,fastqs,feature_types gex1,/path/to/fastqs,Gene Expression abc1,/path/to/fastqs,Antibody Capture mux1,/path/to/fastqs,Multiplexing Capture [samples] sample_id,cmo_ids sample1,CMO301 sample2,CMO303

CMO Reference

The cmo-set option in the [gene-expression] table of the multi config CSV allows you to provide a reference for custom Cell Multiplexing oligos (e.g., antibody TotalSeqA/B/C tags). The design of this reference is nearly identical to the Feature Barcode Reference used to describe Feature Barcodes, with one difference: the feature_type is required to be Multiplexing Capture instead of those feature types supported in the Feature Barcode reference. The id column may contain alphanumeric, underscore, and hyphen characters; special characters like a pipe (|) should not be used in this file (only for separating multiple CMO IDs from the same sample in config CSV).

Default CMO Reference

id,name,read,pattern,sequence,feature_type
CMO301,CMO301,R2,5P(BC),ATGAGGAATTCCTGC,Multiplexing Capture
CMO302,CMO302,R2,5P(BC),CATGCCAATAGAGCG,Multiplexing Capture
CMO303,CMO303,R2,5P(BC),CCGTCGTCCAAGCAT,Multiplexing Capture
CMO304,CMO304,R2,5P(BC),AACGTTAATCACTCA,Multiplexing Capture
CMO305,CMO305,R2,5P(BC),CGCGATATGGTCGGA,Multiplexing Capture
CMO306,CMO306,R2,5P(BC),AAGATGAGGTCTGTG,Multiplexing Capture
CMO307,CMO307,R2,5P(BC),AAGCTCGTTGGAAGA,Multiplexing Capture
CMO308,CMO308,R2,5P(BC),CGGATTCCACATCAT,Multiplexing Capture
CMO309,CMO309,R2,5P(BC),GTTGATCTATAACAG,Multiplexing Capture
CMO310,CMO310,R2,5P(BC),GCAGGAGGTATCAAT,Multiplexing Capture
CMO311,CMO311,R2,5P(BC),GAATCGTGATTCTTC,Multiplexing Capture
CMO312,CMO312,R2,5P(BC),ACATGGTCAACGCTG,Multiplexing Capture

The default CMO reference above is available as a downloadable CSV here.