nf-core/bacass
Simple bacterial assembly and annotation pipeline
2.1.0). The latest
stable release is 2.2.0
.
Define where the pipeline should find input data and save output data.
Path to tab-separated sample sheet
stringPath to sample sheet, either tab-separated (.tsv), comma-separated (.csv), or in YAML format (.yml/.yaml), that points to compressed fastq files.
The sample sheet must have six tab-separated columns/entries with the following headers:
ID(required): Unique sample IDs, must start with a letter, and can only contain letters, numbers or underscoresR1(optional): Paths to (forward) reads zipped FastQ filesR2(optional): Paths to reverse reads zipped FastQ files, required if the data is paired-endLongFastQ(optional): Paths to long reads zipped FastQ filesFast5(optional): Paths to the directory containing FAST5 filesGenomeSize(optional): A number (including decimals) ending with 'm', representing genome size.
Please be aware that files will be required based on the chosen assembly type specified with the '--assembly_type' option, which can be set to one of the following values: ['short', 'long', 'hybrid'].`
The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.
stringEmail 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.
Parameters for QC and trim short-reads
save files that failed to pass trimming thresholds ending in *.fail.fastq.gz
booleansave all merged reads to the a file ending in *.merged.fastq.gz
booleanSkip FastQC
booleanSkip FastP
booleanPath 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.
Allowed technologies for long read assembly : ["-pacbio", "-nanopore", "-pacbio-hifi"]
stringThis 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.
Parameters for the annotation
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.
stringExtra 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`
Path to Bakta database
stringDownload Bakta database
booleanSpecifies 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.
booleanSkip MultiQC
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 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|d|day)\s*)+$Use to set an upper-limit for the time requirement for each process. Should be a string in the format integer-unit e.g. --max_time '2.h'
Less common options for the pipeline, typically set in a config file.
Display help text.
booleanDisplay version and exit.
booleanMethod used to save pipeline results to output directory.
stringThe Nextflow publishDir option specifies which intermediate files should be saved to the output directory. This option tells the pipeline what method should be used to move these files. See Nextflow docs for details.
MultiQC report title. Printed as page header, used for filename if not otherwise specified.
stringEmail address for completion summary, only when pipeline fails.
string^([a-zA-Z0-9_\-\.]+)@([a-zA-Z0-9_\-\.]+)\.([a-zA-Z]{2,5})$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.
booleanIncoming hook URL for messaging service
stringIncoming hook URL for messaging service. Currently, MS Teams and Slack are supported.
Custom config file to supply to MultiQC.
stringCustom logo file to supply to MultiQC. File name must also be set in the MultiQC config file
stringCustom MultiQC yaml file containing HTML including a methods description.
stringBoolean whether to validate parameters against the schema at runtime
booleantrueShow all params when using --help
booleanBy default, parameters set as hidden in the schema are not shown on the command line when a user runs with --help. Specifying this option will tell the pipeline to show all parameters.
Validation of parameters fails when an unrecognised parameter is found.
booleanBy default, when an unrecognised parameter is found, it returns a warinig.
Validation of parameters in lenient more.
booleanAllows string values that are parseable as numbers or booleans. For further information see JSONSchema docs.
A comma separated string of inputs the schema validation should ignore
stringmodules,igenomes_base