Cell Ranger ATAC1.1, printed on 09/07/2024
Cell Ranger ATAC's pipelines analyze sequencing data produced from Chromium Single Cell ATAC libraries. This involves the following steps:
Run cellranger-atac mkfastq on the Illumina® BCL output folder to generate FASTQ files.
Run cellranger-atac count on each library that was demultiplexed by cellranger-atac mkfastq.
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 cellranger-atac mkfastq to generate FASTQ files. For example, if the flowcell serial number was HAWT7ADXX
, then cellranger-atac mkfastq will output FASTQ files in HAWT7ADXX/outs/fastq_path
.
To generate single-cell accessibility counts for a single library, run cellranger-atac count with the following arguments. For a complete list of command-line arguments, run cellranger-atac count --help.
For help on which arguments to use to target a particular set of FASTQs, consult Specifying Input FASTQ Files for 10x Pipelines. |
--indices is deprecated. It is not needed with the output of cellranger-atac mkfastq, or bcl2fastq |
$ cd /home/jdoe/runs $ cellranger-atac count --id=sample345 \ --reference=/opt/refdata-cellranger-atac-GRCh38-1.1.0 \ --fastqs=/home/jdoe/runs/HAWT7ADXX/outs/fastq_path \ --sample=mysample
Following a set of preflight checks to validate input arguments, cellranger-atac count pipeline stages will begin to run:
Martian Runtime - 3.2.1 Running preflight checks (please wait)... 2018-09-17 21:33:47 [runtime] (ready) ID.sample345.SC_ATAC_COUNTER_CS.SC_ATAC_COUNTER._BASIC_SC_ATAC_COUNTER._ALIGNER.SETUP_CHUNKS 2018-09-17 21:33:47 [runtime] (run:local) ID.sample345.SC_ATAC_COUNTER_CS.SC_ATAC_COUNTER._BASIC_SC_ATAC_COUNTER._ALIGNER.SETUP_CHUNKS.fork0.chnk0.main 2018-09-17 21:33:56 [runtime] (chunks_complete) ID.sample345.SC_ATAC_COUNTER_CS.SC_ATAC_COUNTER._BASIC_SC_ATAC_COUNTER._ALIGNER.SETUP_CHUNKS ...
By default, cellranger-atac 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-atac to using up to sixteen cores at once. Similarly,
--localmem
will restrict the amount of memory (in GB) used by
cellranger-atac.
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-atac will assume it is an existing pipestance and attempt to resume running it.
A successful cellranger-atac count run should conclude with a message similar to this:
2018-09-17 22:26:56 [runtime] (join_complete) ID.sample345.SC_ATAC_COUNTER_CS.SC_ATAC_COUNTER.CLOUPE_PREPROCESS Outputs: - Per-barcode fragment counts & metrics: /opt/sample345/outs/singlecell.csv - Position sorted BAM file: /opt/sample345/outs/possorted_bam.bam - Position sorted BAM index: /opt/sample345/outs/possorted_bam.bam.bai - Summary of all data metrics: /opt/sample345/outs/summary.json - HTML file summarizing data & analysis: /opt/sample345/outs/web_summary.html - Bed file of all called peak locations: /opt/sample345/outs/peaks.bed - Raw peak barcode matrix in hdf5 format: /opt/sample345/outs/raw_peak_bc_matrix.h5 - Raw peak barcode matrix in mex format: /opt/sample345/outs/raw_peak_bc_matrix - Directory of analysis files: /opt/sample345/outs/analysis - Filtered peak barcode matrix in hdf5 format: /opt/sample345/outs/filtered_peak_bc_matrix.h5 - Filtered peak barcode matrix: /opt/sample345/outs/filtered_peak_bc_matrix - Barcoded and aligned fragment file: /opt/sample345/outs/fragments.tsv.gz - Fragment file index: /opt/sample345/outs/fragments.tsv.gz.tbi - Filtered tf barcode matrix in hdf5 format: /opt/sample345/outs/filtered_tf_bc_matrix.h5 - Filtered tf barcode matrix in mex format: /opt/sample345/outs/filtered_tf_bc_matrix - Loupe Cell Browser input file: /opt/sample345/outs/cloupe.cloupe - csv summarizing important metrics and values: /opt/sample345/outs/summary.csv 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 |
---|---|
singlecell.csv | Per-barcode fragment counts & metrics |
possorted_bam.bam | Position sorted BAM file |
possorted_bam.bam.bai | Position sorted BAM index |
summary.json | Summary of all data metrics |
web_summary.html | HTML file summarizing data & analysis |
peaks.bed | Bed file of all called peak locations |
raw_peak_bc_matrix.h5 | Raw peak barcode matrix in hdf5 format |
raw_peak_bc_matrix | Raw peak barcode matrix in mex format |
analysis | Directory of analysis files |
filtered_peak_bc_matrix.h5 | Filtered peak barcode matrix in hdf5 format |
filtered_peak_bc_matrix | Filtered peak barcode matrix |
fragments.tsv.gz | Barcoded and aligned fragment file |
fragments.tsv.gz.tbi | Fragment file index |
filtered_tf_bc_matrix.h5 | Filtered tf barcode matrix in hdf5 format |
filtered_tf_bc_matrix | Filtered tf barcode matrix in mex format |
cloupe.cloupe | Loupe Cell Browser input file |
Once cellranger-atac count has successfully completed, you can browse the resulting summary HTML file in any supported web browser, open the .cloupe file in Loupe Cell Browser, or refer to the Understanding Output section to explore the data by hand.