10x Genomics
Chromium Single Cell Gene Expression

Cell Ranger7.1 (latest), printed on 12/03/2024

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
• Command to download a customizable multi config CSV
• Example multi config CSVs
• CMO Reference
• Barcode-sample assignment CSV

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.

3' GEX	3' FB	CellPlex	Use multi?
Yes	Yes	Yes	Required
Yes	Yes	No	Optional. Prefer count
Yes	No	Yes	Required
Yes	No	No	Optional. Prefer count
No	Yes	No	Optional. Prefer 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:

Argument	Description
--id	A unique run ID string: e.g. sample345 that is also the output folder name. Cannot be more than 64 characters.
--csv	Path to config CSV file with input libraries and analysis parameters.

The multi config CSV contains both the library definitions and experimental design variables. It is composed of up to four sections for 3' data:

• The [gene-expression] section has two columns that specify parameters relevant to analysis of gene expression data, such as reference genome and cell-calling parameters, as well as other all-purpose parameters.
• The [feature] section has two columns that specify parameters relevant to analysis of Feature Barcode libraries.
• The [libraries] section has three required columns that specify where the input FASTQ files may be found.
• The [samples] section has two required columns that specify sample information for Cell Multiplexing.

Example formats for different product configurations are below. A template for a multi config CSV can be downloaded here or via the command line. Example multi config CSVs can be downloaded from public datasets here.

Multi Config CSV
Section: [gene-expression]
Field	Description
reference	Required. Path of folder containing 10x Genomics-compatible genome reference.
min-assignment-confidence	Optional. The minimum estimated likelihood to call a sample as tagged with a Cell Multiplexing Oligo (CMO) instead of "Unassigned". Users may wish to tolerate a higher rate of mis-assignment in order to obtain more singlets to include in their analysis, or a lower rate of mis-assignment at the cost of obtaining fewer singlets. By default, this value is 0.9. Contact support@10xgenomics.com for further advice.
cmo-set	Optional. The default CMO reference IDs are built into the Cell Ranger software and do not need to be specified. However, this option can be used to specify the path to a custom CMO set CSV file, declaring CMO constructs and associated barcodes. See CMO Reference section for details.
target-panel	Optional. Path to a Target Panel CSV file or name of a 10x Genomics fixed gene panel (pathway, pan-cancer, immunology, neuroscience). Required for Targeted Gene Expression analysis. Default analysis will exclude intronic mapped reads, which is the recommended mode for targeted assays.
no-target-umi-filter	Optional. Disable targeted UMI filtering stage. See Targeted Algorithms for details. Default: false
r1-length	Optional. Limit the length of the input Read 1 sequence of Gene Expression libraries to the first N bases, where N is a user-supplied value. Note that the length includes the 10x Barcode and UMI sequences so do not set this below 26. This and r2-length are useful options for determining the optimal read length for sequencing. Default: do not trim Read 1.
r2-length	Optional. Limit the length of the input Read 2 sequence of Gene Expression libraries to the first N bases, where N is a user-supplied value. Trimming occurs before sequencing metrics are computed and therefore, limiting the length of Read 2 may affect Q30 scores. Default: do not trim Read 2.
chemistry	Optional. Assay configuration. NOTE: by default, the assay configuration is detected automatically (recommended mode). Users will typically not need to specify a chemistry. Options are: auto for autodetection threeprime for Single Cell 3' SC3Pv1 or SC3Pv2 or SC3Pv3 for Single Cell 3' v1/v2/v3 SC3Pv3HT for Single Cell 3' v3.1 HT SC-FB for Single Cell Antibody-only 3' v2 Default: auto
expect-cells	Optional. Override the pipeline’s auto-estimate. See cell calling algorithm overview for details on how this parameter is used. If used, enter the expected number of recovered cells. Up to 30,000 cells are supported with standard kits for Cell Multiplexing and up to 60,000 cells for HT kits.
force-cells	Optional. Force pipeline to use this number of cells, bypassing cell detection. Default: detect cells using Cell Ranger's cell calling algorithm
include-introns	Optional. Set to false to exclude intronic reads in count. Including introns in analysis is recommended to maximize sensitivity, except when target-panel is used. Default: true
no-secondary	Optional. Disable secondary analysis, e.g. clustering. Default: false
no-bam	Optional. Set this flag to true to skip BAM file generation. This will reduce the total computation time for the pipestance and the size of the output directory. If unsure, we recommend not using this option, as BAM files can be useful for troubleshooting and downstream analysis. Default: false
check-library-compatibility	Optional. This option allows users to disable the check that evaluates 10x Barcode overlap between libraries when multiple libraries are specified (e.g., Gene Expression + Antibody Capture). Setting this option to false will disable the check across all library combinations. We recommend running this check (default), however if the pipeline errors out, users can bypass the check to generate outputs for troubleshooting. Default: true
barcode-sample-assignment	Optional. Path to a barcode-sample assignment CSV file that specifies the barcodes that belong to each sample. See details below to set up this file.
Section: [feature]
Field	Description
reference	Path to the Feature reference CSV file, declaring Feature Barcode constructs and associated barcodes. Required only for Antibody Capture or CRISPR Guide Capture libraries.
r1-length	Optional. Limit the length of the input Read 1 sequence of Feature Barcode libraries (Antibody Capture, CRISPR Guide Capture, Multiplexing Capture) to the first N bases, where N is a user-supplied value. Note that the length includes the 10x Barcode and UMI sequences so do not set this below 26. This and r2-length are useful options for determining the optimal read length for sequencing. Default: do not trim Read 1.
r2-length	Optional. Limit the length of the input Read 2 sequence of Feature Barcode libraries (Antibody Capture, CRISPR Guide Capture, Multiplexing Capture) to the first N bases, where N is a user-supplied value. Trimming occurs before sequencing metrics are computed and therefore, limiting the length of Read 2 may affect Q30 scores. Default: do not trim Read 2.
Section: [libraries](see also Specifying Input FASTQ Files for cellranger multi)
Column	Description
fastq_id	Required. The Illumina sample name to analyze. This will be as specified in the sample sheet supplied to mkfastq or bcl2fastq.
fastqs	Required. Path to the folder containing the FASTQ files to be analyzed. Generally, this will be the fastq_path folder generated by cellranger mkfastq.
feature_types	Required. The underlying feature type of the library, which must be one of: Gene Expression Antibody Capture CRISPR Guide Capture Multiplexing Capture
lanes	Optional. The lanes associated with this sample, separated with a pipe (e.g., 1|2). Default: uses all lanes
physical_library_id	Optional. Library type. NOTE: by default, the library type is detected automatically based on specified feature_types (recommended mode). Users typically do not need to include the physical_library_id column in the CSV file.
subsample_rate	Optional. The rate at which reads from the provided FASTQ files are sampled. Must be strictly greater than 0 and less than or equal to 1.
Section: [samples]
Column	Description
sample_id	A name to identify a multiplexed sample. Must be alphanumeric with hyphens and/or underscores, and less than 64 characters. Required for Cell Multiplexing libraries.
cmo_ids	The Cell Multiplexing oligo IDs used to multiplex this sample. Only input CMOs used in the experiment. If multiple CMOs were used for a sample, separate IDs with a pipe (e.g., CMO301|CMO302). Required for Cell Multiplexing libraries.
description	Optional. A description for the sample.

• 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 - v4.0.8
 
Running preflight checks (please wait)...
...

By default, Cell Ranger 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 Cell Ranger to using up to sixteen cores at once. Similarly, --localmem will restrict the amount of memory (in GB) used by Cell Ranger.

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, Cell Ranger 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.

Command to download a customizable multi config CSV

Cell Ranger v7.1 enables users to download a multi config CSV template by running:

cellranger multi-template --output=/path/to/FILE.csv

Replace code in red with the path to directory in which you wish to output the template. Omitting the file path downloads the file into your working directory. After downloading, please remember to customize the template based on your assay and experimental design.

To print a list and description of all configurable parameters available in cellranger multi, run

cellranger multi-template --parameters

Specifying both --parameters and --output will output a parameter documentation file. Run cellranger multi-template --help or cellranger multi-template -h for more information about available flags.

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.

• 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 [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 [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 [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] section 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).

For example, Cell Ranger's default CMO reference looks like this (built into Cell Ranger):

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.

Barcode-sample assignment CSV

The barcode-sample-assignment option in the [gene-expression] section of the multi config CSV allows users to provide a file that manually specifies the barcodes for each sample. It will override Cell Ranger's default cell calling and tag calling steps, and may be useful in cases where data with microfluidic failures can be partially rescued. This feature allows users to import custom tag calling done via 3rd party tools as well (see the Tag assignment of 10x Genomics CellPlex data using Seurat's HTODemux function Analysis Guide for help).

Here is an example multi config CSV:

[gene-expression]
reference,/path/to/transcriptome
barcode-sample-assignment,/path/to/barcode_sample_assignment.csv

[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

The barcode-sample CSV file has at most two columns, one for the barcode sequence and another that is either the sample ID or the tag assignment. A barcode can only be assigned to one sample; barcodes with multiple sample or tag entries will result in an error in Cell Ranger. Here are two examples:

Option 1: Assign to samples

Barcode,Sample_ID
ACGTACGTACGTACGT-1,Jurkat
CGTACGTACGTACGTA-1,Raji
GTACGTACGTACGTAC-1,Jurkat
TACGTACGTACGTACG-1,Raji
...

Option 2: Assign to tags

Barcode,Assignment
ACGTACGTACGTACGT-1,CMO1
CGTACGTACGTACGTA-1,Multiplet
GTACGTACGTACGTAC-1,Blank
TACGTACGTACGTACG-1,Unassigned
...