nf-core/bacass
Simple bacterial assembly and annotation pipeline
1.0.0
). The latest
stable release is
2.3.1
.
Usage
Table of contents
- Introduction
- Running the pipeline
- Updating the pipeline
- Reproducibility
- Main arguments
- Job resources
- Automatic resubmission
- Custom resource requests
- AWS batch specific parameters
- Other command line parameters
General Nextflow info
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:
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/bacass releases page and find the latest version number - numeric only (eg. 1.3.1
). Then specify this when running the pipeline with -r
(one hyphen) - eg. -r 1.3.1
.
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/bacass
singularity
- A generic configuration profile to be used with Singularity
- Pulls software from DockerHub
test
- A profile with a complete configuration for automated testing
- Includes links to test data so needs no other parameters
--reads
Use this to specify the location of your input FastQ files. For example:
Please note the following requirements:
- The path must be enclosed in quotes
- The path must have at least one
*
wildcard character - When using the pipeline with paired end data, the path must use
{1,2}
notation to specify read pairs.
If left unspecified, a default pattern is used: data/*{1,2}.fastq.gz
See -params-file
for an alternative way to specify read pairs
--skip_kraken2
Skip running Kraken2 classifier on reads.
--kraken2db
Path to Kraken2 database. See Kraken2 homepage for download links. Minikraken2 8GB is a reasonable choice, since we run Kraken here mainly just to check for sample purity.
-params-file
A parameters file, listing parameters defined here, including paired FastQ input if not defined through --reads
.
The format is as follows: {'samples': {sm1: {'readunits': {ru1: {'fq1': p1, 'fq2': p2}, ...}}}, ...}
where sm1 is a sample name, ru1 is a readunit (fastq pair) name,
and p1 and p2 are full paths to FastQ files 1 and 2.
This allows to have multiple samples and multiple FastQ pairs per sample and a file-only
configuration of pipeline behaviour.
This file can also list other parameters as described here (e.g. --kraken2db
)
--unicycler_args
This advanced option allows you to pass extra arguments to Unicycler (e.g. "--mode conservative"
or
"--no_correct"
). For this to work you need to quote the arguments and add at least one space
--prokka_args
This advanced option allows you to pass extra arguments to Prokka (e.g. " --rfam"
or
" --genus name"
). For this to work you need to quote the arguments and add at least one space
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.
--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 speicfy 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.