10x Genomics Support/Cell Ranger 7.2/Getting Started/

What is Cell Ranger?

Cell Ranger is a set of analysis pipelines that process Chromium Next GEM single cell data to align reads, generate feature-barcode matrices, perform clustering and other secondary analysis, and more (see list of example workflows and supported libraries). Cell Ranger includes five pipelines relevant to the 3' Single Cell Gene Expression and 5' Immune Profiling Solutions:

  • cellranger mkfastq demultiplexes raw base call (BCL) files generated by Illumina sequencers into FASTQ files. It is a wrapper around Illumina's bcl2fastq, with additional features that are specific to 10x Genomics libraries and a simplified sample sheet format. Illumina's bcl2fastq or BCL Convert may also be used to generate FASTQ files.

  • cellranger count takes FASTQ files and performs alignment, filtering, barcode counting, and UMI counting. It uses the Chromium cellular barcodes to generate feature-barcode matrices, determine clusters, and perform gene expression analysis. The count pipeline can take input from multiple sequencing runs on the same GEM well. cellranger count also processes Feature Barcode data alongside Gene Expression reads.

  • cellranger multi is used to analyze Cell Multiplexing, Fixed RNA Profiling, and Antigen Capture (BEAM) data. It takes FASTQ files from a combination of Gene Expression, Feature Barcode, and V(D)J libraries generated from a single GEM well. cellranger multi performs alignment, filtering, barcode counting, and UMI counting. It uses the Chromium cellular barcodes to generate feature-barcode matrices, determine clusters, and perform gene expression analysis. It is the recommended pipeline for analyzing a combination of 5' Gene Expression and V(D)J libraries (with or without Feature Barcode libraries) sequenced from the same sample. It is the only available pipeline for analyzing 3' Cell Multiplexing, Fixed RNA Profiling, and 5' Antigen Capture (BEAM) data.

  • cellranger vdj takes FASTQ files for V(D)J libraries and performs sequence assembly and paired clonotype calling. It uses the Chromium cellular barcodes and UMIs to assemble V(D)J transcripts per cell. Clonotypes and CDR3 sequences are output as a .vloupe file which can be loaded into Loupe V(D)J Browser.

  • cellranger aggr aggregates outputs from multiple runs of cellranger count, cellranger vdj, or cellranger multi, normalizing those runs to the same sequencing depth and then recomputing the feature-barcode matrices and analysis on the combined data. The aggr pipeline can be used to combine data from multiple samples into an experiment-wide feature-barcode matrix and analysis.

  • cellranger reanalyze takes feature-barcode matrices produced by cellranger count, cellranger multi, or cellranger aggr and reruns the dimensionality reduction, clustering, and gene expression algorithms using tunable parameter settings.

  1. Run Cell Ranger on 10x Genomics Cloud Analysis

    Skip Cell Ranger download and installation and get started with 10x Genomics Cloud Analysis, our recommended method for running Cell Ranger pipelines for most new customers. Use your web browser to easily generate Cell Ranger outputs from your FASTQ files and aggregate outputs from multiple runs, free for every 10x Genomics sample. Currently available only in the United States and Canada. Sign up for a free account or view tutorials and learn more.

  2. Install and run Cell Ranger on your own computing infrastructure

    Learn how to install and run Cell Ranger.

If you are beginning with raw base call (BCL) files, the Cell Ranger workflow starts with demultiplexing the BCL files for each flow cell directory. You may use cellranger mkfastq or one of Illumina's demultiplexing software. If you are beginning with FASTQ files that have already been demultiplexed, you can skip the demultiplexing step and begin with cellranger count. Please see the Specifying Input FASTQ pages for guidelines on which arguments to use for your scenario.

The exact steps of the workflow vary depending on how many samples, GEM wells, and flow cells you have, and whether you are including data from Feature Barcode, Cell Multiplexing, or Fixed RNA Profiling kits. This section describes a few possible workflows.

Watch a webinar on getting started with single cell data analysis.

In this example, one sample is processed through one GEM well and sequenced on one flow cell. In this case, generate FASTQs using cellranger mkfastq and run cellranger count as described in Single-Sample Analysis.

This example also illustrates two sequencing libraries. A single GEM well can yield multiple physical libraries: one Gene Expression library and one or more Feature Barcode libraries.

In this example, one sample is processed through one GEM well, resulting in one library which is sequenced across multiple flow cells. This workflow is commonly performed to increase sequencing depth. In this case, all reads can be combined in a single instance of the cellranger count or multi pipeline. This process is described in the Specifying Input FASTQ pages.

Here, one sample is processed through multiple GEM wells. This is typically done when conducting technical replicate experiments. The libraries from the GEM wells are then pooled onto one flow cell and sequenced. In this case, demultiplex the data from the sequencing run with cellranger mkfastq, then run the libraries from each GEM well through a separate instance of cellranger count. Then you can perform a combined analysis using cellranger aggr, as described in Multi-Library Aggregation.

In this example, multiple samples are processed through multiple GEM wells, which generate multiple libraries and are pooled onto one flow cell. After demultiplexing, you must run cellranger count separately for each GEM well; if you have two GEM wells, then run cellranger count twice. Then you can aggregate them with a single instance of cellranger aggr, as described in Multi-Library Aggregation.

Cell Ranger 6.0 introduces support for analyzing Cell Multiplexing data. In this case, multiple samples are uniquely tagged with Cell Multiplexing Oligos (CMOs), enabling multiple samples to be pooled in a single GEM well. This results in a CMO and Gene Expression (GEX) library for each GEM well. After generating your FASTQ files, run the cellranger multi pipeline on the combined FASTQ data for the GEX and CMO libraries.


Cell Ranger 7.0 introduces support for analyzing Fixed RNA Profiling (FRP) Gene Expression data. In this case, multiple samples are uniquely tagged with Probe Barcodes, enabling samples to be pooled in a single GEM well, resulting in one Gene Expression library. After generating FASTQ files, run the cellranger multi pipeline.

Library support by Cell Ranger version is summarized in the tables below.

3' Single Cell and FLEXCR 7.2CR 7.1CR 7.0CR 6.1CR 6.0CR 5.0CR 4.0CR 3.1CR 3.0CR 2.2
3’ Gene Expression v2 Libraries
3’ Gene Expression v3 Libraries-
3’ Gene Expression v3 + Cell Surface Protein Libraries-
3’ Gene Expression v3 + CRISPR Screening Libraries Expression-
3’ Cell Surface Protein Libraries only--
3’ Targeted Gene Expression----
3’ Cell Multiplexing-----
3’ LT (Low Throughput)------
3’ HT (High Throughput)------
Fixed RNA ProfilingCR 7.2CR 7.1CR 7.0
Gene expression (singleplex or multiplex)
Gene expression + Antibody Capture (singleplex)
Single cell FFPE Gene Expression (singleplex or multiplex)-
Gene expression + Antibody Capture (multiplex)--
5' Immune ProfilingCR 7.2CR 7.1CR 7.0CR 6.1CR 6.0CR 5.0CR 4.0CR 3.1CR 3.0CR 2.2
5’ Gene Expression
5’ V(D)J
5’ Gene Expression + V(D)J
5’ Gene Expression + Cell Surface Protein-
5’ Gene Expression + Cell Surface Protein + V(D)J-
V(D) J + Cell Surface Protein-
5’ Cell Surface Protein only--
5’ Targeted Gene Expression----
5’ HT (High Throughput)-------
5’ Gene Expression + CRISPR-------
5’ Gene Expression + CRISPR + Cell Surface Protein-------
5’ Gene Expression + CRISPR + V(D)J-------
5’ Gene Expression + Antigen Capture + V(D)J ± Cell Surface Protein--------