nf-core/bacass
Simple bacterial assembly and annotation pipeline
2.0.0). The latest
stable release is 2.2.0
.
Define where the pipeline should find input data and save output data.
Path to comma-separated file containing information about the samples in the experiment.
string^\S+\.csv$You will need to create a design file with information about the samples in your experiment before running the pipeline. Use this parameter to specify its location. It has to be a tab-separated file with 6 columns, and a header row. See usage docs.
For example:
--input 'design_hybrid.csv'
An example of properly formatted input files can be found at the nf-core/test-datasets.
For example, this is the input used for a hybrid assembly in testing:
ID R1 R2 LongFastQ Fast5 GenomeSize
ERR044595 https://github.com/nf-core/test-datasets/raw/bacass/ERR044595_1M_1.fastq.gz https://github.com/nf-core/test-datasets/raw/bacass/ERR044595_1M_2.fastq.gz https://github.com/nf-core/test-datasets/raw/bacass/nanopore/subset15000.fq.gz NA 2.8m
ID: The identifier to use for handling the dataset e.g. sample nameR1: The forward reads in case of available short-read dataR2: The reverse reads in case of available short-read dataLongFastQ: The long read FastQ file with reads in FASTQ formatFast5: The folder containing the basecalled fast5 filesGenomeSize: The expected genome size of the assembly. Only used by the canu assembler.
Missing values (e.g. Fast5 folder in case of short reads) can be omitted by using a NA in the TSV file. The pipeline will handle such cases appropriately then.
Path to the output directory where the results will be saved.
string./resultsEmail address for completion summary.
string^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$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.
Path to Kraken2 database.
stringSee Kraken2 homepage for download
links. Minikraken2 8GB is a reasonable choice, since we run Kraken here mainly just to check for
sample purity.
Parameters for the assembly
The assembler to use for assembly. Available options are Unicycler, Canu, Miniasm. The latter two are only available for long-read data, whereas Unicycler can be used for short or hybrid assembly projects.
stringunicyclerWhich type of assembly to perform.
stringshortThis adjusts the type of assembly done with the input data and can be any of long, short or hybrid. Short & Hybrid assembly will always run Unicycler, whereas long-read assembly can be configured separately using the --assembler parameter.
Extra arguments for Unicycler
stringThis 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.
This can be used to supply extra options to the Canu assembler. Will be ignored when other assemblers are used.
stringWhich assembly polishing method to use.
stringmedakaCan be used to define which polishing method is used by default for long reads. Default is medaka, available options are nanopolish or medaka.
The annotation method to annotate the final assembly. Default choice is prokka, but the dfast tool is also available. For the latter, make sure to create your specific config if you're not happy with the default one provided. See #dfast_config to find out how.
stringprokkaExtra arguments for prokka annotation tool.
stringThis 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 between the arguments. Example:
--prokka_args `--rfam --genus Escherichia Coli`
Specifies a configuration file for the DFAST annotation method.
stringassets/test_config_dfast.pyThis can be used instead of PROKKA if required to specify a specific config file for annotation. If you want to know how to create your config file, please refer to the DFAST readme on how to create one. The default config (assets/test_config_dfast.py) is just included for testing, so if you want to annotate using DFAST, you have to create a config!
Skip running Kraken2 classifier on reads.
booleanSkip annotating the assembly with Prokka /DFAST.
booleanSkip running PycoQC on long read input.
booleanSkip polishing the long-read assembly with fast5 input. Will not affect short/hybrid assemblies.
booleanParameters used to describe centralised config profiles. These should not be edited.
Git commit id for Institutional configs.
stringmasterBase directory for Institutional configs.
stringhttps://raw.githubusercontent.com/nf-core/configs/masterIf 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 this parameter.
Institutional configs hostname.
stringInstitutional config name.
stringInstitutional config description.
stringInstitutional config contact information.
stringInstitutional config URL link.
stringSet the top limit for requested resources for any single job.
Maximum number of CPUs that can be requested for any single job.
integer16Use to set an upper-limit for the CPU requirement for each process. Should be an integer e.g. --max_cpus 1
Maximum amount of memory that can be requested for any single job.
string128.GB^\d+(\.\d+)?\.?\s*(K|M|G|T)?B$Use to set an upper-limit for the memory requirement for each process. Should be a string in the format integer-unit e.g. --max_memory '8.GB'
Maximum amount of time that can be requested for any single job.
string240.h^(\d+\.?\s*(s|m|h|day)\s*)+$Use to set an upper-limit for the time requirement for each process. Should be a string in the format integer-unit e.g. --max_time '2.h'
Less common options for the pipeline, typically set in a config file.
Display help text.
booleanMethod used to save pipeline results to output directory.
stringThe Nextflow publishDir option specifies which intermediate files should be saved to the output directory. This option tells the pipeline what method should be used to move these files. See Nextflow docs for details.
MultiQC report title. Printed as page header, used for filename if not otherwise specified.
stringEmail address for completion summary, only when pipeline fails.
string^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$An email address to send a summary email to when the pipeline is completed - ONLY sent if the pipeline does not exit successfully.
Send plain-text email instead of HTML.
booleanFile size limit when attaching MultiQC reports to summary emails.
string25.MB^\d+(\.\d+)?\.?\s*(K|M|G|T)?B$Do not use coloured log outputs.
booleanCustom config file to supply to MultiQC.
stringDirectory to keep pipeline Nextflow logs and reports.
string${params.outdir}/pipeline_infoBoolean whether to validate parameters against the schema at runtime
booleantrueShow all params when using --help
booleanRun this workflow with Conda. You can also use '-profile conda' instead of providing this parameter.
booleanInstead of directly downloading Singularity images for use with Singularity, force the workflow to pull and convert Docker containers instead.
booleanThis may be useful for example if you are unable to directly pull Singularity containers to run the pipeline due to http/https proxy issues.