Long Ranger2.0, printed on 11/14/2024
Long Ranger's Exome Mode analyzes sequencing data from a Chromium-prepared, targeted library. This involves the following steps:
Run longranger demux on the Illumina BCL output folder to generate FASTQ files.
Run longranger run on each exome sample that was demultiplexed by longranger 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 longranger demux to generate FASTQ files. For example, if the flowcell serial number was HAWT7ADXX
, then longranger demux will output FASTQ files in HAWT7ADXX/outs/fastq_path
.
To run Long Ranger in exome mode, use the longranger run command with a .bed file as the --targets argument. Here is a complete example:
Argument | Description |
---|---|
--id | A unique run ID string: e.g. sample345 |
--sex | Sex of the sample: male or female |
--fastqs | Path of the FASTQ folder generated by longranger demux, e.g. /home/jdoe/runs/HAWT7ADXX/outs/fastq_path |
--reference | Path to a 10x compatible reference, e.g. /opt/refdata-hg19-2.0.0 .See Installation for how to download and install the default reference. |
--targets | BED file associated with the pulldown used for this Chromium library e.g. /home/jdoe/runs/agilent_exome.bed |
--indices | (optional) Sample indices associated with this sample. Comma-separated list of:
|
--fastqprefix | (optional) Sample name as specified in the sample sheet supplied to bcl2fastq . See Demultiplexing with bcl2fastq for more information. |
--lanes | (optional) Lanes associated with this sample |
After determining these input arguments, run longranger run:
$ cd /home/jdoe/runs $ longranger run --id=sample345 \ --sex=female \ --fastqs=/home/jdoe/runs/HAWT7ADXX/outs/fastq_path \ --reference=/opt/refdata-hg19-2.0.0 \ --targets=/home/jdoe/runs/agilent_exome.bed \ --indices=SI-GA-A1
Following a set of preflight checks to validate input arguments, Long Ranger pipeline stages will begin to run:
longranger run 2.0.1 Copyright (c) 2016 10x Genomics, Inc. All rights reserved. ----------------------------------------------------------------------------- Martian Runtime - 2.0.1 Running preflight checks (please wait)... 2016-05-01 12:00:00 [runtime] (ready) ID.sample345.PHASER_SVCALLER_CS.PHASER_SVCALLER._ALIGNER.SETUP_CHUNKS 2016-05-01 12:00:00 [runtime] (run:local) ID.sample345.PHASER_SVCALLER_CS.PHASER_SVCALLER._SNPINDEL_PHASER.SORT_GROUND_TRUTH 2016-05-01 12:00:00 [runtime] (run:local) ID.sample345.PHASER_SVCALLER_CS.PHASER_SVCALLER._SNPINDEL_PHASER.SORT_GROUND_TRUTH.fork0.chnk0.main ...
By default, longranger run 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 Long Ranger to using up to sixteen cores at once. Similarly,
--localmem
will restrict the amount of memory (in GB) used by
longranger run.
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, Long Ranger will assume it is an existing pipestance and attempt to resume running it.
A successful longranger run execution should conclude with a message similar to this:
2016-05-02 15:46:41 [runtime] (run:local) ID.sample345.PHASER_SVCALLER_CS.PHASER_SVCALLER.LOUPE_PREPROCESS.fork0.join 2016-05-02 15:46:44 [runtime] (join_complete) ID.sample345.PHASER_SVCALLER_CS.PHASER_SVCALLER.LOUPE_PREPROCESS 2016-05-02 15:46:55 [runtime] VDR killed 4738 files, 223GB. Outputs: - Run summary: /home/jdoe/runs/sample345/outs/summary.csv - BAM barcoded: /home/jdoe/runs/sample345/outs/phased_possorted_bam.bam - BAM index: /home/jdoe/runs/sample345/outs/phased_possorted_bam_index.bam.bai - VCF phased: /home/jdoe/runs/sample345/outs/phased_variants.vcf.gz - VCF index: /home/jdoe/runs/sample345/outs/phased_variants_index.vcf.gz.tbi - SV calls: /home/jdoe/runs/sample345/outs/sv_calls.bedpe - SV candidates: /home/jdoe/runs/sample345/outs/sv_candidates.bedpe - SV phasing: /home/jdoe/runs/sample345/outs/sv_phasing.tsv - Loupe file: /home/jdoe/runs/sample345/outs/loupe.loupe 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 |
---|---|
summary.csv | Run summary metrics in CSV format |
phased_possorted_bam.bam | Aligned reads annotated with barcode information |
phased_possorted_bam_index.bam.bai | Index for phased_possorted_bam.bam |
phased_variants.vcf.gz | VCF annotated with barcode and phasing information |
phased_variants_index.vcf.gz.tbi | Index for phased_variants.vcf.gz |
sv_calls.bedpe | Confidently called structural variants |
sv_candidates.bedpe | Structural variant candidates failing one or more filters |
sv_phasing.tsv | Structural variant phasing information |
loupe.loupe | File that can be opened in the Loupe genome browser |
Once longranger run has successfully completed, you can browse the resulting .loupe
file in the Loupe genome browser, or refer to the Understanding Output section to explore the data by hand.