nf-core/vipr
Assembly and intrahost / low-frequency variant calling for viral samples
22.10.6
.
Learn more.
nf-core/vipr Usage
Please refer to the Nextflow documentation for generic Nextflow options, like -resume
etc.
General Nextflow info
Nextflow handles job submissions on compute 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
using input paramters as defined in params.yaml
. See below for more
information about profiles.
Note that the pipeline will create the following files in your working directory:
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/vipr releases page
and find the latest version number - numeric only (e.g. 1.0
). Then
specify this when running the pipeline with -r
(one hyphen),
e.g. -r 1.0
.
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
-params-file
You can modify program behaviour and specify input files in a yaml
configuration file. An example is given in example_params.yaml
.
Please note: this is currently the only way to specify read input. The corresponding entries in params.yaml looks as follows:
So you can specify multiple samples and each samples can contain multiple fastq pairs (AKA readunits)
-profile
Use this parameter to choose a configuration profile. Each profile is designed for a different compute environment - follow the links below to see instructions for running on that system. Available profiles are:
standard
- The default profile, used if
-profile
is not specified at all. Runs locally and expects all software to be installed and available on thePATH
. - This profile is mainly designed to be used as a starting point for other configurations and is inherited by most of the other profiles.
- The default profile, used if
none
- No configuration at all. Useful if you want to build your own config from scratch and want to avoid loading in the default
base
config profile (not recommended).
- No configuration at all. Useful if you want to build your own config from scratch and want to avoid loading in the default
See nextflow.config
for more available profiles
--skip-kraken
Skips the optional Kraken metagenomics classifaction of your reads.
Reference Genomes
The pipeline requires you to specify close reference for samples
(--ref-fasta
, e.g. Zika) and a fasta reference for decontamination
(--cont-fasta
e.g. human) If you in addition also use Kraken (see
above) you will need to specify the path to your Kraken database (--kraken-db
).
You can add the above parameters to your params-file (see above). Then entries looks as follows
An example is given in example_params.yaml
.
--outdir
The output directory where the results will be saved.
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 in conf
for examples.