Cell Ranger1.0, printed on 12/21/2024
Cell Ranger's cellranger pipeline analyzes sequencing data produced from Chromium single cell 3’ RNA-seq libraries. This involves the following steps:
Run cellranger demux on the Illumina BCL output folder to generate FASTQ files.
Run cellranger run on each sample that was demultiplexed by cellranger demux.
For the following example, assume that the Illumina BCL output is in a folder named /sequencing/140101_D00123_0111_AHAWT7ADXX.
First, follow the instructions on running the demultiplexer to generate FASTQ files. For example, if the flowcell serial number was HAWT7ADXX, then cellranger demux will output FASTQ files in HAWT7ADXX/outs/fastq_path.
To run cellranger, simply specify the following arguments:
| Argument | Description |
|---|---|
--id | A unique run ID string: e.g. sample345 |
--transcriptome | Path to the Cell Ranger compatible transcriptome reference e.g.
|
--fastqs | Path of the FASTQ folder generated by cellranger demux e.g. /home/jdoe/runs/HAWT7ADXX/outs/fastq_path |
--indices | (optional) Sample indices associated with this sample. Comma-separated list of:
|
--lanes | (optional) Lanes associated with this sample |
--fastqprefix | (optional) Sample name as specified in the sample sheet supplied to bcl2fastq. See Demultiplexing with bcl2fastq for more information. |
--cells | (optional) Expected number of recovered cells |
--localcores | Restricts cellranger run to use specified number of cores to execute pipeline stages. By default, cellranger will use all of the cores available on your system. |
--localmem | Restricts cellranger run to use specified amount of memory (in GB) to execute pipeline stages. By default, cellranger will use 90% of the memory available on your system. Please note that cellranger requires at least 16 GB of memory to run all pipeline stages. |
After determining these input arguments, run cellranger:
$ cd /home/jdoe/runs $ cellranger run --id=sample345 \ --transcriptome=/opt/refdata-cellranger-1.0.0/hg19 \ --fastqs=/home/jdoe/runs/HAWT7ADXX/outs/fastq_path \ --indices=SI-3A-A1 \ --cells=1000
Following a set of preflight checks to validate input arguments, cellranger run pipeline stages will begin to run:
Martian Runtime - 1.3.0 Running preflight checks (please wait)... 2016-02-22 14:23:52 [runtime] (ready) ID.sample345.CELLRANGER_CS.CELLRANGER.SETUP_CHUNKS 2016-02-22 14:23:55 [runtime] (split_complete) ID.sample345.CELLRANGER_CS.CELLRANGER.SETUP_CHUNKS 2016-02-22 14:23:55 [runtime] (run:local) ID.sample345.CELLRANGER_CS.CELLRANGER.SETUP_CHUNKS.fork0.chnk0.main ...
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 sample ID you specified (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 run should conclude with a message similar to this:
2016-02-23 12:10:09 [runtime] (join_complete) ID.sample345.CELLRANGER_CS.CELLRANGER.SUMMARIZE_REPORTS Outputs: - Genome-aligned BAM: /opt/sample345/outs/possorted_genome_bam.bam - Genome-aligned BAM index: /opt/sample345/outs/possorted_genome_bam_index.bam.bai - Run summary HTML: /opt/sample345/outs/web_summary.html - Run summary CSV: /opt/sample345/outs/metrics_summary.csv - Unfiltered gene-barcode matrices: /opt/sample345/outs/raw_gene_bc_matrices - Filtered gene-barcode matrices: /opt/sample345/outs/filtered_gene_bc_matrices - Matrix analysis: /opt/sample345/outs/analysis - Per-molecule read information: /opt/sample345/outs/molecule_info.h5 Pipestance completed successfully!
The output of the pipeline will be contained in a folder named with the sample ID you specified (e.g. sample345). The subfolder named outs will contain the main pipeline output files:
| File Name | Description |
|---|---|
possorted_genome_bam.bam | Reads aligned to the genome and transcriptome annotated with barcode information |
possorted_genome_bam_index.bam.bai | Index for possorted_genome_bam.bam |
web_summary.html | Run summary metrics and charts in HTML format |
metrics_summary.csv | Run summary metrics in CSV format |
raw_gene_bc_matrices | Unfiltered gene-barcode matrices containing all barcodes in MEX format |
filtered_gene_bc_matrices | Filtered gene-barcode matrices containing only cellular barcodes in MEX format |
analysis | Initial secondary analysis data including dimensionality reduction, cell clustering, and differential expression |
molecule_info.h5 | Per-read molecule information used for downsampling |
Once cellranger has successfully completed, you can browse the resulting summary HTML file in any supported web browser, or refer to the Understanding Output section to explore the data by hand.