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Cell Ranger


Loupe

10x Genomics
Chromium Single Cell Gene Expression

Targeted Gene Expression Analysis

Table of Contents

Overview

Targeted Gene Expression technology uses selected panels of relevant targeted genes. When analyzing Targeted Gene Expression data, Cell Ranger requires a Target Panel CSV file as an input file.

Target Panel CSV

Target Panel CSV files corresponding to predesigned gene panels can be found within the target_panels/ directory in the Cell Ranger package. For example, if you installed Cell Ranger to /opt/cellranger-5.0.0, then the target panel CSVs will be contained in /opt/cellranger-5.0.0/target_panels. These CSV files can also be downloaded on the Panel Selection page, along with more detailed information about each panel.

Detailed documentation on this file format can be found here along with descriptions of all other downloads provided for target gene panels.

Targeted Gene Expression analysis

Cell Ranger performs analysis of single cell Targeted Gene Expression data with the cellranger count and multi pipelines. Cell Ranger provides the same interface and features for both Targeted and Whole Transcriptome Analysis (WTA) Gene Expression data, as described in Single-Library Analysis with Cell Ranger.

To enable Targeted Gene Expression analysis in cellranger count, specify the relevant Target Panel CSV file using the --target-panel flag:

cd /home/jdoe/runs
cellranger count --id=sample345 \
                   --target-panel=/opt/cellranger-5.0.0/target_panels/immunology_v1.0_GRCh38-2020-A.target_panel.csv \
                   --transcriptome=/opt/refdata-gex-GRCh38-2020-A \
                   --fastqs=/home/jdoe/runs/HAWT7ADXX/outs/fastq_path \
                   --sample=mysample \
                   --localcores=8 \
                   --localmem=64

For Targeted Gene Expression data, targeted UMI filtering is performed after the usual UMI Counting step. This additional filtering is only active for sequencing libraries with very high depth, in which spurious molecules can be observed in a very small fraction of reads. Targeted UMI filtering can be disabled when --target-panel is used with the --no-target-umi-filter flag, although this is not recommended.

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.

Targeted Gene Expression and Antibody Capture and CRISPR Guide Capture analysis

To analyze Targeted Gene Expression with Antibody Capture or CRISPR Guide Capture libraries, you can use the cellranger count pipeline. See Feature Barcode Analysis for details about generating the libraries CSV and the feature reference CSV files. In addition to the flag specifying the target panel file described above, you'll also need to add flags for Feature Barcode information. For this analysis, the FASTQ file paths and sample information are specified in the libraries CSV file. For example (replace text in red with correct file paths):

cellranger count --id=sample345 \
                 --target-panel=/opt/cellranger-5.0.0/target_panels/immunology_v1.0_GRCh38-2020-A.target_panel.csv \
                 --transcriptome=/opt/refdata-gex-GRCh38-2020-A \
                 --libraries=/path/to/library.csv \
                 --feature-ref=/path/to/feature_ref.csv \
                 --localcores=8 \
                 --localmem=64

Targeted Gene Expression and Cell Multiplexing analysis

To analyze Targeted Gene Expression with 3' Cell Multiplexing libraries, use the cellranger multi pipeline. An example dataset is available for multiplexed mouse samples sequenced with a target neuroscience gene panel. See Cell Multiplexing with cellranger multi for details about generating the multi config CSV file. For example (replace text in red with correct file paths):

[gene-expression]
reference,/path/to/refdata-gex-mm10-2020-A
target-panel,/path/to/target_panel.csv
 
[libraries]
fastq_id,fastqs,feature_types
targeted_gex,/path/to/fastqs,Gene Expression
cellplex,/path/to/fastqs,Multiplexing Capture
 
[samples]
sample_id,cmo_ids
sample1,CMO301
sample2,CMO304

Then, run Cell Ranger:

cellranger multi --id=sample345 --csv=/path/to/multi_config_csv.csv