nf-core/sarek
Analysis pipeline to detect germline or somatic variants (pre-processing, variant calling and annotation) from WGS / targeted sequencing
2.5
). The latest
stable release is
3.5.0
.
Introduction
Nextflow handles job submissions on SLURM or other environments, and supervises running the jobs.
Thus the Nextflow process must run until the pipeline is finished.
We recommend that you put the process running in the background through screen
/ tmux
or similar tool.
Alternatively you can run nextflow within a cluster job submitted your job scheduler.
It is recommended to limit the Nextflow Java virtual machines memory.
We recommend adding the following line to your environment (typically in ~/.bashrc
or ~./bash_profile
):
Running the pipeline
The typical command for running the pipeline is as follows:
This will launch the pipeline with the docker
configuration profile.
See below for more information about profiles.
Note that the pipeline will create the following files in your working directory:
The nf-core/sarek pipeline comes with more documentation about running the pipeline, found in the docs/
directory:
* Extra Documentation on variant calling
* Extra Documentation on annotation
Updating the pipeline
When you run the above command, Nextflow automatically pulls the pipeline code from GitHub and stores it as a cached version. When running the pipeline after this, it will always use the cached version if available - even if the pipeline has been updated since. To make sure that you’re running the latest version of the pipeline, make sure that you regularly update the cached version of the pipeline:
Reproducibility
It’s a good idea to specify a pipeline version when running the pipeline on your data. This ensures that a specific version of the pipeline code and software are used when you run your pipeline. If you keep using the same tag, you’ll be running the same version of the pipeline, even if there have been changes to the code since.
First, go to the nf-core/sarek releases page and find the latest version number - numeric only (eg. 2.5.0
).
Then specify this when running the pipeline with -r
(one hyphen) - eg. -r 2.5.0
.
This version number will be logged in reports when you run the pipeline, so that you’ll know what you used when you look back in the future.
Main arguments
-profile
Use this parameter to choose a configuration profile.
Profiles can give configuration presets for different compute environments.
Note that multiple profiles can be loaded, for example: -profile docker
- the order of arguments is important!
If -profile
is not specified at all the pipeline will be run locally and expects all software to be installed and available on the PATH
.
awsbatch
- A generic configuration profile to be used with AWS Batch.
conda
docker
- A generic configuration profile to be used with Docker
- Pulls software from dockerhub:
nfcore/sarek
singularity
- A generic configuration profile to be used with Singularity
- Pulls software from DockerHub:
nfcore/sarek
test
- A profile with a complete configuration for automated testing
- Includes links to test data so needs no other parameters
--input
Use this to specify the location of your input TSV file, on mapping
, recalibrate
and variantcalling
steps.
For example:
Multiple TSV files can be specified if the path must be enclosed in quotes
Use this to specify the location to a directory on mapping
step with a single germline sample only.
For example:
Use this to specify the location of your VCF input file on annotate
step.
For example:
Multiple VCF files can be specified if the path must be enclosed in quotes
--sample
⚠️ This params is deprecated — it will be removed in a future release. Please check:
--input
Use this to specify the location of your input TSV file, on mapping
, recalibrate
and variantcalling
steps.
For example:
Multiple TSV files can be specified if the path must be enclosed in quotes
Use this to specify the location to a directory on mapping
step with a single germline sample only.
For example:
Use this to specify the location of your VCF input file on annotate
step.
For example:
Multiple VCF files can be specified if the path must be enclosed in quotes
--sampleDir
⚠️ This params is deprecated — it will be removed in a future release. Please check:
--input
Use this to specify the location to a directory on mapping
step with a single germline sample only.
For example:
--annotateVCF
⚠️ This params is deprecated — it will be removed in a future release. Please check:
--input
Use this to specify the location of your VCF input file on annotate
step.
For example:
Multiple VCF files can be specified if the path must be enclosed in quotes
--noGVCF
Use this to disable g.vcf from HaplotypeCaller
.
--skipQC
Use this to disable specific QC and Reporting tools.
Available: all
, bamQC
, BCFtools
, FastQC
, MultiQC
, samtools
, vcftools
, versions
Default: None
--noReports
⚠️ This params is deprecated — it will be removed in a future release. Please check:
--skipQC
Use this to disable all QC and Reporting tools.
--nucleotidesPerSecond
Use this to estimate of how many seconds it will take to call variants on any interval, the default value is 1000
is it’s not specified in the <intervals>.bed
file.
--step
Use this to specify the starting step:
Default mapping
Available: mapping
, recalibrate
, variantcalling
and annotate
--tools
Use this to specify the tools to run:
Available: ASCAT
, ControlFREEC
, FreeBayes
, HaplotypeCaller
, Manta
, mpileup
, MuTect2
, Strelka
, TIDDIT
--noStrelkaBP
Use this not to use Manta
candidateSmallIndels
for Strelka
as Best Practice.
--targetBED
Use this to specify the target BED file for targeted or whole exome sequencing.
Reference genomes
The pipeline config files come bundled with paths to the illumina iGenomes reference index files. If running with docker or AWS, the configuration is set up to use the AWS-iGenomes resource.
--genome
(using iGenomes)
There are 2 different species supported by Sarek in the iGenomes references.
To run the pipeline, you must specify which to use with the --genome
flag.
You can find the keys to specify the genomes in the iGenomes config file. Genomes that are supported are:
- Human
--genome GRCh37
--genome GRCh38
Note that you can use the same configuration setup to save sets of reference files for your own use, even if they are not part of the iGenomes resource. See the Nextflow documentation for instructions on where to save such a file.
The syntax for this reference configuration is as follows:
--acLoci
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--acLociGC
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--bwaIndex
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--chrDir
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--chrLength
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--dbsnp
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--dbsnpIndex
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--dict
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--fasta
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--fastaFai
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--genomeDict
⚠️ This params is deprecated — it will be removed in a future release. Please check:
--dict
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--genomeFile
⚠️ This params is deprecated — it will be removed in a future release. Please check:
--fasta
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--genomeIndex
⚠️ This params is deprecated — it will be removed in a future release. Please check:
--fastaFai
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--germlineResource
The germline resource VCF file (bgzipped and tabixed) needed by GATK4 Mutect2 is a collection of calls that are likely present in the sample, with allele frequencies. The AF info field must be present. You can find a smaller, stripped gnomAD VCF file (most of the annotation is removed and only calls signed by PASS are stored) in the iGenomes Annotation/GermlineResource folder. To add your own germline resource supply
--germlineResourceIndex
Tabix index of the germline resource specified at --germlineResource
.
To add your own germline resource supply
--intervals
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--knownIndels
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--knownIndelsIndex
If you prefer, you can specify the full path to your reference genome when you run the pipeline:
--pon
When a panel of normals PON is defined, you will get filtered somatic calls as a result. Without PON, there will be no calls with PASS in the INFO field, only an unfiltered VCF is written. It is recommended to make your own panel-of-normals, as it depends on sequencer and library preparation. For tests in iGenomes there is a dummy PON file in the Annotation/GermlineResource directory, but it should not be used as a real panel-of-normals file. Provide your PON by:
If the PON file is bgzipped, there has to be a tabixed index file at the same directory.
--snpeffDb
If you prefer, you can specify the DB version when you run the pipeline:
--vepCacheVersion
If you prefer, you can specify the cache version when you run the pipeline:
--igenomesIgnore
Do not load igenomes.config
when running the pipeline.
You may choose this option if you observe clashes between custom parameters and those supplied in igenomes.config
.
Job resources
Automatic resubmission
Each step in the pipeline has a default set of requirements for number of CPUs, memory and time.
For most of the steps in the pipeline, if the job exits with an error code of 143
(exceeded requested resources) it will automatically resubmit with higher requests (2 x original, then 3 x original).
If it still fails after three times then the pipeline is stopped.
Custom resource requests
Wherever process-specific requirements are set in the pipeline, the default value can be changed by creating a custom config file.
See the files hosted at nf-core/configs
for examples.
If you are likely to be running nf-core
pipelines regularly it may be a good idea to request that your custom config file is uploaded to the nf-core/configs
git repository.
Before you do this please can you test that the config file works with your pipeline of choice using the -c
parameter (see definition below).
You can then create a pull request to the nf-core/configs
repository with the addition of your config file, associated documentation file (see examples in nf-core/configs/docs
), and amending nfcore_custom.config
to include your custom profile.
If you have any questions or issues please send us a message on Slack.
AWS Batch specific parameters
Running the pipeline on AWS Batch requires a couple of specific parameters to be set according to your AWS Batch configuration.
Please use the -awsbatch
profile and then specify all of the following parameters.
--awsqueue
The JobQueue that you intend to use on AWS Batch.
--awsregion
The AWS region to run your job in.
Default is set to eu-west-1
but can be adjusted to your needs.
Please make sure to also set the -w/--work-dir
and --outdir
parameters to a S3 storage bucket of your choice - you’ll get an error message notifying you if you didn’t.
Other command line parameters
--outdir
The output directory where the results will be saved. Default: `results/
--sequencing_center
The sequencing center that will be used in the BAM CN field
--email
Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits.
If set in your user config file (~/.nextflow/config
) then you don’t need to specify this on the command line for every run.
-name
Name for the pipeline run. If not specified, Nextflow will automatically generate a random mnemonic.
This is used in the MultiQC report (if not default) and in the summary HTML / e-mail (always).
NB: Single hyphen (core Nextflow option)
-resume
Specify this when restarting a pipeline. Nextflow will used cached results from any pipeline steps where the inputs are the same, continuing from where it got to previously.
You can also supply a run name to resume a specific run: -resume [run-name]
.
Use the nextflow log
command to show previous run names.
NB: Single hyphen (core Nextflow option)
-c
Specify the path to a specific config file (this is a core NextFlow command).
NB: Single hyphen (core Nextflow option)
Note - you can use this to override pipeline defaults.
--custom_config_version
Provide git commit id for custom Institutional configs hosted at nf-core/configs
.
This was implemented for reproducibility purposes.
Default is set to master
.
--custom_config_base
If you’re running offline, nextflow will not be able to fetch the institutional config files
from the internet.
If you don’t need them, then this is not a problem.
If you do need them, you should download the files from the repo and tell nextflow where to find them with the custom_config_base
option.
For example:
Note that the nf-core/tools helper package has a
download
command to download all required pipeline files + singularity containers + institutional configs in one go for you, to make this process easier.
--max_memory
Use to set a top-limit for the default memory requirement for each process.
Should be a string in the format integer-unit eg. --max_memory '8.GB'
--max_time
Use to set a top-limit for the default time requirement for each process.
Should be a string in the format integer-unit eg. --max_time '2.h'
--max_cpus
Use to set a top-limit for the default CPU requirement for each process.
Should be a string in the format integer-unit eg. --max_cpus 1
--plaintext_email
Set to receive plain-text e-mails instead of HTML formatted.
--monochrome_logs
Set to disable colourful command line output and live life in monochrome.
--multiqc_config
Specify a path to a custom MultiQC configuration file.