Define where the pipeline should find input data and save output data.

Path to comma-separated file containing information sample names and paths to corresponding FASTA files.

required
type: string
pattern: ^\S+\.csv$

Before running the pipeline, you will need to create a design file with information about the samples to be scanned by nf-core/funcscan, containing sample name and path/to/your/contigs.fasta. Use this parameter to specify its location. It has to be a comma-separated file with 2 columns, and a header row (sample, fasta). See usage docs.

The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.

required
type: string

Email address for completion summary.

type: string
pattern: ^([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.

MultiQC report title. Printed as page header, used for filename if not otherwise specified.

type: string

These parameters influence which workflow (ARG, AMP and/or BGC) to activate.

Activate antimicrobial peptide screening tools.

type: boolean

Activate antimicrobial resistance gene screening tools.

type: boolean

Activate biosynthetic gene cluster screening tools.

type: boolean

These options influence the generation of annotation files required for downstream steps in ARG, AMP, and BGC workflows.

Specify which annotation tool to use for some downstream tools.

type: string

Specify whether to save gene annotations in the results directory.

type: boolean

These parameters influence the annotation algorithm of Bacteria used by BAKTA.

Specify a path to BAKTA database.

type: string

Specify a path to a database that is prepared in a BAKTA format.

Download full or light version of the Bakta database if not supplying own database.

type: string

If you want the pipeline to download the Bakta database for you, you can choose between the full (33.1 GB) and light (1.3 GB) version. The full version is generally recommended for best annotation results, because it contains all of these:

  • UPS: unique protein sequences identified via length and MD5 hash digests (100% coverage & 100% sequence identity)
  • IPS: identical protein sequences comprising seeds of UniProt's UniRef100 protein sequence clusters
  • PSC: protein sequences clusters comprising seeds of UniProt's UniRef90 protein sequence clusters
  • PSCC: protein sequences clusters of clusters comprising annotations of UniProt's UniRef50 protein sequence clusters

If download bandwidth, storage, memory, or run duration requirements become an issue, go for the light version (which only contains PSCCs) by modifying the annotation_bakta_db_downloadtype flag.
More details can be found in the documentation

Modifies tool parameter(s):

  • BAKTA_DBDOWNLOAD: --type

Use the default genome-length optimised mode (rather than the metagenome mode).

type: boolean

By default, Bakta's --meta mode is used in the pipeline to improve the gene prediction of highly fragmented metagenomes.

By specifying this parameter Bakta will instead use its default mode that is optimised for singular 'complete' genome sequences.

More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --meta

Specify the minimum contig size.

type: integer
default: 1

Specify the minimum contig size that would be annotated by BAKTA.
If run with '--annotation_bakta_compliant', the minimum contig length must be set to 200. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --min-contig-length

Specify the genetic code translation table.

type: integer
default: 11

Specify the genetic code translation table used for translation of nucleotides to amino acids.
All possible genetic codes (1-25) used for gene annotation can be found here. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --translation-table

Specify the type of bacteria to be annotated to detect signaling peptides.

type: string

Specify the type of bacteria expected in the input dataset for correct annotation of the signal peptide predictions. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --gram

Specify that all contigs are complete replicons.

type: boolean

This flag expects contigs that make up complete chromosomes and/or plasmids. By calling it, the user ensured that the contigs are complete replicons. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --complete

Changes the original contig headers.

type: boolean

This flag specifies that the contig headers should be rewritten. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --keep-contig-headers

Clean the result annotations to standardise them to Genbank/ENA conventions.

type: boolean

The resulting annotations are cleaned up to standardise them to Genbank/ENA/DDJB conventions. CDS without any attributed hits and those without gene symbols or product descriptions different from hypothetical will be marked as 'hypothetical'.
When activated the '--min-contig-length' will be set to 200. More info can be found here.

Modifies tool parameter(s):

  • BAKTA: --compliant

Activate tRNA detection & annotation.

type: boolean

This flag activates tRNAscan-SE 2.0 that predicts tRNA genes. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --skip-trna

Activate tmRNA detection & annotation.

type: boolean

This flag activates Aragorn that predicts tmRNA genes. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --skip-tmrna
    `

Activate rRNA detection & annotation.

type: boolean

This flag activates Infernal vs. Rfam rRNA covariance models that predicts rRNA genes. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --rrna

Activate ncRNA detection & annotation.

type: boolean

This flag activates Infernal vs. Rfam ncRNA covariance models that predicts ncRNA genes.
BAKTA distinguishes between ncRNA genes and (cis-regulatory) regions to enable the distinction of feature overlap detection.
This including distinguishing between ncRNA gene types: sRNA, antisense, ribozyme and antitoxin. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --ncrna

Activate ncRNA region detection & annotation.

type: boolean

This flag activates Infernal vs. Rfam ncRNA covariance models that predicts ncRNA cis-regulatory regions.
BAKTA distinguishes between ncRNA genes and (cis-regulatory) regions to enable the distinction of feature overlap detection.
This including distinguishing between ncRNA (cis-regulatory) region types: riboswitch, thermoregulator, leader and frameshift element. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --skip-ncrna-region

Activate CRISPR array detection & annotation.

type: boolean

This flag activates PILER-CR that predicts CRISPR arrays. More details can be found in the documentation.

Modifies tool parameter(s):

  • BAKTA: --skip-crispr

Skip CDS detection & annotation.

type: boolean

This flag skips CDS prediction that is done by PYRODIGAL with which the distinct prediction for complete replicons and uncompleted contigs is done.
For more information on how BAKTA predicts CDS please refer to BAKTA documentation.

Modifies tool parameter(s):

  • BAKTA: --skip-cds

Activate pseudogene detection & annotation.

type: boolean

This flag activates the search for reference Phytochelatin Synthase genes (PCSs) using hypothetical CDS as seed sequences, then aligns the translated PCSs against up-/downstream-elongated CDS regions. For more info refer to BAKTA documentation.

Modifies tool parameter(s):

  • BAKTA: --skip-pseudo

Skip sORF detection & annotation.

type: boolean

Skip the prediction of sORFs from amino acids stretches as less than 30aa. For more info please refer to BAKTA documentation. All sORF without gene symbols or product descriptions different from hypothetical will be discarded, while only those identified hits exhibiting proper gene symbols or product descriptions different from hypothetical will still be included in the final annotation.

Modifies tool parameter(s):

  • BAKTA: --skip-sorf

Activate gap detection & annotation.

type: boolean

Activates any gene annotation found within contig assembly gaps. For more info. please refer to BAKTA documentation.

Modifies tool parameter(s):

  • BAKTA: --skip-gap

Activate oriC/oriT detection & annotation.

type: boolean

Activates the BAKTA search for oriC/oriT genes by comparing results from Blast+ (generated by cov=0.8, id=0.8) and the MOB-suite of oriT & DoriC oriC/oriV sequences. Annotations of ori regions take into account overlapping Blast+ hits and are conducted based on a majority vote heuristic. Region edges may be fuzzy. For more info please refer to the BAKTA documentation.

Modifies tool parameter(s):

  • BAKTA: --skip-ori

Activate generation of circular genome plots.

type: boolean

Activate this flag to generate genome plots (might be memory-intensive).

Modifies tool parameter(s):

  • BAKTA: --skip-plot

These parameters influence the annotation algorithm used by Prokka.

Use the default genome-length optimised mode (rather than the metagenome mode).

type: boolean

By default, Prokka's --metagenome mode is used in the pipeline to improve the gene prediction of highly fragmented metagenomes.

By specifying this parameter Prokka will instead use its default mode that is optimised for singular 'complete' genome sequences.

For more information, please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --metagenome

Suppress the default clean-up of the gene annotations.

type: boolean

By default, annotation in Prokka is carried out by alignment to other proteins in its database, or the databases the user provides via the tools --proteins flag. The resulting annotations are then cleaned up to standardise them to Genbank/ENA conventions.
'Vague names' are set to 'hypothetical proteins', 'possible/probable/predicted' are set to 'putative' and 'EC/CPG and locus tag ids' are removed.

By supplying this flag you stop such clean up leaving the original annotation names.

For more information please check Prokka documentation.

This flag suppresses this default behavior of Prokka (which is to perform the cleaning).

Modifies tool parameter(s):

  • Prokka: --rawproduct

Specify the kingdom that the input represents.

type: string

Specifies the kingdom that the input sample is derived from and/or you wish to screen for

⚠️ Prokka cannot annotate Eukaryotes.

For more information please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --kingdom

Specify the translation table used to annotate the sequences.

type: integer
default: 11

Specify the translation table used to annotate the sequences. All possible genetic codes (1-25) used for gene annotation can be found here. This flag is required if the flag --kingdom is assigned.

For more information please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --gcode

Minimum contig size required for annotation (bp).

type: integer
default: 1

Specify the minimum contig lengths to carry out annotations on. The Prokka developers recommend that this should be >= 200 bp, if you plan to submit such annotations to NCBI.

For more information please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --mincontiglen

Minimum e-value cut-off.

type: number
default: 0.000001

Specifiy the minimum e-value used for filtering the alignment hits.

For more information please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --evalue

Set the assigned minimum coverage.

type: integer
default: 80

Specify the minimum coverage percent of the annotated genome. This must be set between 0-100.

For more information please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --coverage

Allow transfer RNA (trRNA) to overlap coding sequences (CDS).

type: boolean

Allow transfer RNA (trRNA) to overlap coding sequences (CDS). Transfer RNAs are short stretches of nucleotide sequences that link mRNA and the amino acid sequence of proteins. Their presence helps in the annotation of the sequences, because each trRNA can only be attached to one type of amino acid.

For more information please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --cdsrnaolap

Use RNAmmer for rRNA prediction.

type: boolean

Activates RNAmmer instead of the Prokka default Barrnap for rRNA prediction during the annotation process. RNAmmer classifies ribosomal RNA genes in genome sequences by using two levels of Hidden Markov Models. Barrnap uses the nhmmer tool that includes HMMER 3.1 for HMM searching in RNA:DNA style.

For more information please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --rnammer

Force contig name to Genbank/ENA/DDJB naming rules.

type: boolean
default: true

Force the contig headers to conform to the Genbank/ENA/DDJB contig header standards. This is activated in combination with --centre [X] when contig headers supplied by the user are non-conforming and therefore need to be renamed before Prokka can start annotation. This flag activates --genes --mincontiglen 200. For more information please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --compliant

Add the gene features for each CDS hit.

type: boolean

For every CDS annotated, this flag adds the gene that encodes for that CDS region. For more information please check Prokka documentation.

Modifies tool parameter(s):

  • Prokka: --addgenes

Retains contig names.

type: boolean

This parameter allows prokka to retain the original contig names by activating PROKKA's --force flag. If this parameter is set to false it activates PROKKA's flags --locus-tag PROKKA --centre CENTER so the locus tags (contig names) will be PROKKA_# and the center tag will be CENTER. By default PROKKA changes contig headers to avoid errors that might rise due to long contig headers, so this must be turned on if the user has short contig names that should be retained by PROKKA.

Modifies tool parameter(s):

  • Prokka: --locus-tag PROKKA --centre CENTER
  • Prokka: --force

These parameters influence the annotation algorithm used by Prodigal.

Specify whether to use Prodigal's single-genome mode for long sequences.

type: boolean

By default Prodigal runs in 'single genome' mode that requires sequence lengths to be equal or longer than 20000 characters.

However, more fragmented reads from MAGs often result in contigs shorter than this. Therefore, nf-core/funcscan will run with the meta mode by default, but providing this parameter allows to override this and run in single genome mode again.

For more information check Prodigal documentation.

Modifies tool parameter(s):
-PRODIGAL: -p

Does not allow partial genes on contig edges.

type: boolean

Suppresses partial genes from being on contig edge, resulting in closed ends. Should only be activated for genomes where it is sure the first and last bases of the sequence(s) do not fall inside a gene. Run together with -p normal (former -p single) .

For more information check Prodigal documentation.

Modifies tool parameter(s):

  • PRODIGAL: -c

Specifies the translation table used for gene annotation.

type: integer
default: 11

Specifies which translation table should be used for seqeunce annotation. All possible genetic code translation tables can be found here. The default is set at 11, which is used for standard Bacteria/Archeae.

For more information check Prodigal documentation.

Modifies tool parameter(s):

  • PRODIGAL: -g

Forces Prodigal to scan for motifs.

type: boolean

Forces PRODIGAL to a full scan for motifs rather than activating the Shine-Dalgarno RBS finder, the default scanner for PRODIGAL to train for motifs.

For more information check Prodigal documentation.

Modifies tool parameter(s):

  • PRODIGAL: -n

These parameters influence the annotation algorithm used by Pyrodigal.

Specify whether to use Pyrodigal's single-genome mode for long sequences.

type: boolean

By default Pyrodigal runs in 'single genome' mode that requires sequence lengths to be equal or longer than 20000 characters.

However, more fragmented reads from MAGs often result in contigs shorter than this. Therefore, nf-core/funcscan will run with the meta mode by default, but providing this parameter allows to override this and run in single genome mode again.

For more information check Pyrodigal documentation.

Modifies tool parameter(s):
-PYRODIGAL: -p

Does not allow partial genes on contig edges.

type: boolean

Suppresses partial genes from being on contig edge, resulting in closed ends. Should only be activated for genomes where it is sure the first and last bases of the sequence(s) do not fall inside a gene. Run together with -p single .

For more information check Pyrodigal documentation.

Modifies tool parameter(s):

  • PYRODIGAL: -c

Specifies the translation table used for gene annotation.

type: integer
default: 11

Specifies which translation table should be used for seqeunce annotation. All possible genetic code translation tables can be found here. The default is set at 11, which is used for standard Bacteria/Archeae.

For more information check Pyrodigal documentation.

Modifies tool parameter(s):

  • PYRODIGAL: -g

Forces Pyrodigal to scan for motifs.

type: boolean

Forces Pyrodigal to a full scan for motifs rather than activating the Shine-Dalgarno RBS finder, the default scanner for Pyrodigal to train for motifs.

For more information check Pyrodigal documentation.

Modifies tool parameter(s):

  • PYRODIGAL: -n

Generic options for database downloading

Specify whether to save pipeline-downloaded databases in your results directory.

type: boolean

While nf-core/funcscan can download databases for you, often these are very large and can significantly slow-down pipeline runtime if the databases have to be downloaded every run.

Specifying --save_databases while save the pipeline-downloaded databases in your results directory. This applies to: BAKTA, DeepBGC, DeepARG, AMRFinderPlus, antiSMASH, and DRAMP.

You can then move the resulting directories/files to a central cache directory of your choice for re-use in the future.

If you do not specify these flags, the database files will remain in your work/ directory and will be deleted if cleanup = true is specified in your config, or if you run nextflow clean.

Antimicrobial Peptide detection using a deep learning model.

Skip AMPlify during AMP-screening.

type: boolean

Antimicrobial Peptide detection using machine learning

Skip AMPir during AMP-screening.

type: boolean

Specify which machine learning classification model to use.

type: string

AMPir uses a supervised statistical machine learning approach to predict AMPs. It incorporates two support vector machine classification models, "precursor" and "mature".

The precursor module is better for predicted proteins from a translated transcriptome or translated gene models. The alternative model (mature) is best suited for AMP sequences after post-translational processing, typically from direct proteomic sequencing.

More information can be found in the AMPir documentation.

Modifies tool parameter(s):

  • AMPir: model =

Specify minimum protein length for prediction calculation.

type: integer
default: 10

Filters result for minimum protein length.
Note that amino acid sequences that are shorter than 10 amino acids long and/or contain anything other than the standard 20 amino acids are not evaluated and will contain an NA as their prob_AMP value

More information can be found in the AMPir documentation.

Modifies tool parameter(s):

  • AMPir parameter: min_length in the calculate_features() function

Antimicrobial Peptide detection based on predefined HMM models

Skip HMMsearch during AMP-screening.

type: boolean

Specify path to the AMP hmm model file(s) to search against. Must have quotes if wildcard used.

type: string

HMMSearch performs biosequence analysis using profile hidden Markov Models.
The models are specified in.hmm files that are specified with this parameter

e.g.

--amp_hmmsearch_models '/<path>/<to>/<models>/*.hmm'  

You must wrap the path in quotes if you use a wildcard, to ensure Nextflow expansion not bash!

For more information check HMMER documentation.

Saves a multiple alignment of all significant hits to a file.

type: boolean

Save a multiple alignment of all significant hits (those satisfying inclusion thresholds) to a file

For more information check HMMER documentation.

Modifies tool parameter(s):

  • HMMsearch: -A

Save a simple tabular file summarising the per-target output.

type: boolean

Save a simple tabular (space-delimited) file summarizing the per-target output, with one data line per homologous target sequence found.

For more information check HMMER documentation.

Modifies tool parameter(s)

  • HMMsearch: --tblout

Save a simple tabular file summarising the per-domain output.

type: boolean

Save a simple tabular (space-delimited) file summarizing the per-domain output, with one data line per homologous domain detected in a query sequence for each homologous model.

For more information check HMMER documentation.

Modifies tool parameter(s):

  • HMMsearch: --domtblout

Antimicrobial Peptide detection mining from metagenomes

Skip Macrel during AMP-screening.

type: boolean

AntiMicrobial Peptides parsing and functional classification tool

Path to AMPcombi reference database directory (DRAMP).

type: string

AMPcombi uses the 'general AMPs' dataset of the (DRAMP database)[http://dramp.cpu-bioinfor.org/downloads/] for taxonomic classification. If you have a local version of it, you can provide the path to the folder containing the reference database files:

  1. a fasta file with a .fasta file extension
  2. the corresponding table with with functional and taxonomic classifications in .tsv file extension.

For more information check AMPcombi documentation.

Specify probability cutoff to filter AMPs

type: number

Specify the minimum probability an AMP hit must have to be retained in the final output file. Anything below this threshold will be removed.

For more information check AMPcombi documentation.

Modifies tool parameter(s):

  • AMPCOMBI: --cutoff

Antimicrobial resistance gene detection based on NCBI's curated Reference Gene Database and curated collection of Hidden Markov Models

Skip AMRFinderPlus during the ARG-screening.

type: boolean

Specify the path to a local version of the ARMfinderPlus database.

type: string

Specify the path to a local version of the ARMFinderPlus database. If no input is given, the pipeline will download the database for you.

See the nf-core/funcscan usage documentation for more information.

Minimum percent identity to reference sequence.

type: number
default: -1

Specify the minimum percentage amino-acid identity to reference protein or nucleotide identity for nucleotide reference must have if a BLAST alignment (based on methods: BLAST or PARTIAL) was detected, otherwise NA.

If you specify -1, this means use a curated threshold if it exists and 0.9 otherwise.

Setting this value to something other than -1 will override any curated similarity cutoffs. For BLAST: alignment is > 90% of length and > 90% identity to a protein in the AMRFinderPlus database. For PARTIAL: alignment is > 50% of length, but < 90% of length and > 90% identity to the reference, and does not end at a contig boundary.

For more information check AMRFinderPlus documentation.

Modifies tool parameter(s):

  • AMRFinderPlus: --ident_min

Minimum coverage of the reference protein.

type: number
default: 0.5

Minimum proportion of reference gene covered for a BLAST-based hit analysis if a BLAST alignment was detected, otherwise NA.

For BLAST-based hit analysis: alignment is > 90% of length and > 90% identity to a protein in the AMRFinderPlus database or for PARTIAL: alignment is > 50% of length, but < 90% of length and > 90% identity to the reference, and does not end at a contig boundary.

For more information check AMRFinderPlus documentation.

Modifies tool parameter(s):

  • AMRFinderPlus: --coverage_min

Specify which NCBI genetic code to use for translated BLAST.

type: integer
default: 11

NCBI genetic code for translated BLAST. Number from 1 to 33 to represent the translation table used for BLASTX.

See translation table for more details on which table to use.

For more information check AMRFinderPlus documentation.

Modifies tool parameter(s):

  • AMRFinderPlus: --translation_table

Add the plus genes to the report.

type: boolean

Provide results from "Plus" genes in the output files.

Mostly the plus genes are an expanded set of genes that are of interest in pathogens. This set includes stress response (biocide, metal, and heat resistance), virulence factors, some antigens, and porins. These "plus" proteins have primarily been added to the database with curated BLAST cutoffs, and are generally identified by BLAST searches. Some of these may not be acquired genes or mutations, but may be intrinsic in some organisms. See AMRFinderPlus database for more details.

Modifies tool parameter(s):

  • AMRFinderPlus: --plus

Add identified column to AMRFinderPlus output.

type: boolean

Prepend a column containing an identifier for this run of AMRFinderPlus. For example this can be used to add a sample name column to the AMRFinderPlus results. If set to true, the --name <identifier> is the sample name.

Modifies tool parameter(s):

  • AMRFinderPlus: --name

Antimicrobial resistance gene detection using a deep learning model

Skip DeepARG during the ARG-screening.

type: boolean

Specify the path to the DeepARG database.

type: string

Specify the path to a local version of the DeepARG database (see the pipelines' usage documentation). If no input is given, the module will download the database for you, however this is not recommended, as the database is large and this will take time.

Specify the numeric version number of a user supplied DeepaRG database.

type: integer
default: 2

The DeepARG tool itself does not report explicit the database version it uses. We assume the latest version (as downloaded by the tool's database download module), however if you supply a different database, you must supply the version with this parameter for use with the downstream hAMRonization tool.

The version number must be without any leading v etc.

Specify which model to use (short or long sequences).

type: string

Specify which model to use: short sequences for reads (SS), or long sequences for genes (LS). In the vast majority of cases we recommend using the LS model when using funcscan

For more information check DeepARG documentation.

Modifies tool parameter(s):

  • DeepARG: --model

Specify minimum probability cutoff under which hits are discarded.

type: number
default: 0.8

Sets the minimum probability cutoff below which hits are discarded.

For more information check DeepARG documentation.

Modifies tool parameter(s):

  • DeepARG: --min-prob

Specify E-value cutoff under which hits are discarded.

type: number
default: 1e-10

Sets the cutoff value for Evalue below which hits are discarded

For more information check DeepARG documentation.

Modifies tool parameter(s):

  • DeepARG: --arg-alignment-evalue

Specify percent identity cutoff for sequence alignment under which hits are discarded.

type: integer
default: 50

Sets the value for Identity cutoff for sequence alignment

For more information check DeepARG documentation.

Modifies tool parameter(s):

  • DeepARG: --arg-alignment-identity

Specify alignment read overlap.

type: number
default: 0.8

Sets the value for the allowed alignment read overlap.

For more information check DeepARG documentation.

Modifies tool parameter(s):

  • DeepARG: --arg-alignment-overlap

Specify minimum number of alignments per entry for DIAMOND step of DeepARG.

type: integer
default: 1000

Sets the value of minimum number of alignments per entry for DIAMOND.

For more information check DeepARG documentation.

Modifies tool parameter(s):

  • DeepARG: --arg-num-alignments-per-entry

Antimicrobial resistance gene detection using a deep learning model

Skip fARGene during the ARG-screening.

type: boolean

Specify comma-separated list of which pre-defined HMM models to screen against

type: string
default: class_a,class_b_1_2,class_b_3,class_c,class_d_1,class_d_2,qnr,tet_efflux,tet_rpg,tet_enzyme

Specify via a comma separated list any of the hmm-models of the pre-defined models:
- Class A beta-lactamases: class_a
- Subclass B1 and B2 beta-lactamases: class_b_1_2
- Subclass B3 beta-lactamases: class_b_3
- Class C beta-lactamases: class_c - Class D beta-lactamases: class_d_1, class_d_2 - qnr:qnr - Tetracycline resistance genestet_efflux, tet_rpg, tet_enzyme`

For more information check fARGene documentation.

For example: --arg_fargenemodel 'class_a,qnr,tet_enzyme'

Modifies tool parameter(s):

  • fARGene: --hmm-model

Specify to save intermediate temporary files to results directory.

type: boolean

fARGene generates many additional temporary files which in most cases won't be useful and thus by default are not saved to the pipeline's result directory.

By specifying this parameter, the directories tmpdir/, hmmsearchresults/ and spades_assemblies/ will be also saved in the output directory for closer inspection by the user, if necessary.

The threshold score for a sequence to be classified as a (almost) complete gene.

type: number

The threshold score for a sequence to be classified as a (almost) complete gene. If not pre-assigned, it is assigned by the hmm_model used based on the trade-off between sensitivity and specificity.

For more details see code documentation.

Modifies tool parameter(s):

  • fARGene: --score

The minimum length of a predicted ORF retrieved from annotating the nucleotide sequences.

type: integer
default: 90

The minimum length of a predicted ORF retrieved from annotating the nucleotide sequences. By default the pipeline assigns this to 90% of the assigned hmm_model sequence length.

For more information check fARGene documentation.

Modifies tool parameter(s):

  • fARGene: --min-orf-length

Defines which ORF finding algorithm to use.

type: boolean

By default, pipeline uses prodigal/prokka for the prediction of ORFs from nucleotide sequences. Another option is the NCBI ORFfinder tool that is built into fARGene, the use of which is activated by this flag.

For more information check fARGene documentation.

Modifies tool parameter(s):

  • fARGene: --orf-finder

The translation table/format to use for sequence annotation.

type: string
default: pearson

The translation format that transeq should use for amino acid annotation from the nucleotide sequences. More sequence formats can be found in transeq 'input sequence formats'.

For more information check fARGene documentation.

Modifies tool parameter(s):

  • fARGene: --translation-format

Antimicrobial resistance gene detection, based on alignment to the CARD database

Skip RGI during the ARG-screening.

type: boolean

Save RGI output .json file.

type: boolean

When activated, this flag saves the .json file in the RGI output directory. The .json file contains the ARG predictions in a format that can be can be uploaded to the CARD website for visualization. See RGI documentation for more details. By default, the .json file is generated in the working directory but not saved in the results directory to save disk space (.json file is quite large and not required downstream in the pipeline).

Specify to save intermediate temporary files the results directory.

type: boolean

RGI generates many additional temporary files which in most cases won't be useful so by default are not saved.

By specifying this parameter, the files including temp in the name will be also saved in the output directory for closer inspection by the user, if necessary.

Specify the alignment tool to be used.

type: string

Specifies the alignment tool to be used. By default RGI runs BLAST and this is also set as default in the nf-core/funcscan pipeline. Using this flag the user can activate the alignment by DIAMOND again.

For more information check RGI documentation.

Modifies tool parameter(s):

  • RGI: --alignment_tool

Include all of loose, strict and perfect hits (i.e. >=95% identity) found by RGI.

type: boolean
default: true

When activated it includes 'Loose' hits (a.k.a. Discovery) in addition to strict and perfect hits. All 'Loose' matches of 95% identity or better are automatically listed as 'Strict', regardless of alignment length (RGI v. <6.0.0). This behaviour can be overrun by using the --exclude_nudge flag. The 'Loose' algorithm works outside of the detection model cut-offs to provide detection of new, emergent threats and more distant homologs of AMR genes, but will also catalog homologous sequences and spurious partial matches that may not have a role in AMR.

For more information check RGI documentation.

Modifies tool parameter(s):

  • RGI: --include_loose

Suppresses the default behaviour of RGI with --arg_rgi_includeloose.

type: boolean
default: true

This flag suppresses the default behaviour of RGI with --include_loose, which lists all 'Loose' matches of >= 95% identity as 'Strict', regardless of alignment length. With this strict and perfect labels are added. This is discontinued in future versions of RGI.

For more information check RGI documentation.

Modifies tool parameter(s):

  • RGI: --exclude_nudge

Include screening of low quality contigs for partial genes.

type: boolean

This flag should be used only when the contigs are of poor quality (e.g. short) to predict partial genes.

For more information check RGI documentation.

Modifies tool parameter(s):

  • RGI: --low_quality

Specify a more specific data-type of input (e.g. plasmid, chromosome)

type: string

This flag is used to specify the data type used as input to RGI. By default this is set as 'NA', which makes no assumptions on input data.

For more information check RGI documentation.

Modifies tool parameter(s):

  • RGI: --data

Antimicrobial resistance gene detection, based on alignment to CBI, CARD, ARG-ANNOT, Resfinder, MEGARES, EcOH, PlasmidFinder, Ecoli_VF and VFDB.

Skip ABRicate during the ARG-screening.

type: boolean

Specify which of the provided public databases to use by ABRicate.

type: string

Specifies which database to use from dedicated list of databases available by ABRicate.

For more information check ABRicate documentation.

Modifies tool parameter(s):

  • ABRicate: --db

Minimum percent identity of alignment required for a hit to be considered.

type: integer
default: 80

Specifies the minimum percent identity used to classify an ARG hit using BLAST alignment.

For more information check ABRicate documentation.

Modifies tool parameter(s):

  • ABRicate: --minid

Minimum percent coverage of alignment required for a hit to be considered.

type: integer
default: 80

Specifies the minimum coverage of the nucleotide sequence to be assigned an ARG hit using BLAST alignment. In the ABRicate matrix, an absent gene is assigned (.) and if present, it is assigned the estimated coverage (#).

For more information check ABRicate documentation.

Modifies tool parameter(s):

  • ABRicate: --mincov

Biosynthetic gene cluster detection

Skip antiSMASH during the BGC screening

type: boolean

Path to user-defined local antiSMASH database.

type: string

It is recommend to pre-download the antiSMASH databases to your machine and pass the path of it to this parameter, as this can take a long time to download - particularly when running lots of pipeline runs.

See the pipeline documentation for details on how to download this. If running with docker or singularity, please also check --bgc_antismash_installationdirectory for important information.

Path to user-defined local antiSMASH directory. Only required when running with docker/singularity.

type: string

This is required when running with docker and singularity (not required for conda), due to attempted 'modifications' of files during database checks in the installation directory, something that cannot be done in immutable docker/singularity containers.

Therefore, a local installation directory needs to be mounted (including all modified files from the downloading step) to the container as a workaround.

Minimum longest-contig length a sample must have to be screened with antiSMASH.

type: integer
default: 1000

This specifies the minimum length that the longest contig must have for the entire sample to be screened by antiSMASH.

Any samples that do not reach this length will be not be sent to antiSMASH, therefore you will not receive output for these samples in your --outdir.

⚠️ This is not the same as --bgc_antismash_contigminlength, which specifies to only analyse contigs above that threshold but within a sample that has already passed --bgc_antismash_sampleminlength sample filter!

Minimum length a contig must have to be screened with antiSMASH.

type: integer
default: 1000

This specifies the minimum length that a contig must have for the contig to be screened by antiSMASH.

For more information see the antiSMASH documentation.

This will only apply to samples that are screened with antiSMASH (i.e., those samples that have not been removed by --bgc_antismash_sampleminlength).

You may wish to increase this value compared to that of --bgc_antismash_sampleminlength, in cases where you wish to screen higher-quality (i.e., longer) contigs, or speed up runs by not screening lower quality/less informative contigs.

Modifies tool parameter(s):

  • antiSMASH: --minlength

Turn on clusterblast comparison against database of antiSMASH-predicted clusters.

type: boolean

Compare identified clusters against a database of antiSMASH-predicted clusters using the clusterblast algorithm.

For more information see the antiSMASH documentation.

Modifies tool parameter(s):

  • antiSMASH: --cb-general

Turn on clusterblast comparison against known gene clusters from the MIBiG database.

type: boolean

This will turn on comparing identified clusters against known gene clusters from the MIBiG database using the clusterblast algorithm.

MIBiG is a curated datbase of experimentally characterised gene clusters and with rich associated metadata.

For more information see the antiSMASH documentation.

Modifies tool parameter(s):

  • antiSMASH: --cb-knownclusters

Turn on clusterblast comparison against known subclusters responsible for synthesising precursors.

type: boolean

Turn on additional screening for operons involved in the biosynthesis of early secondary metabolites components using the clusterblast algorithm.

For more information see the antiSMASH documentation.

Modifies tool parameter(s):

  • antiSMASH: --cb-subclusters

Turn on ClusterCompare comparison against known gene clusters from the MIBiG database.

type: boolean

Turn on comparison of detected genes against the MIBiG database using the ClusterCompare algorithm - an alternative to clusterblast.

Note there will not be a dedicated ClusterCompare output in the antiSMASH results directory, but is present in the HTML.

For more information see the antiSMASH documentation.

Modifies tool parameter(s):

  • antiSMASH: --cc-mibig

Generate phylogenetic trees of secondary metabolite group orthologs.

type: boolean

Turning this on will activate the generation of additional functional and phyogenetic analysis of genes, via comparison against databases of protein orthologs.

For more information see the antiSMASH documentation.

Modifies tool parameter(s):

  • antiSMASH: --cb-smcog-trees

Defines which level of strictness to use for HMM-based cluster detection

type: string

Defines which level of strictness to use for HMM-based cluster detection.

These correspond to screening of different groups of 'how well-defined' clusters are. For example, loose will include screening for 'poorly defined' clusters (e.g. saccharides), relaxed for partially present clusters (e.g. certain types of NRPS), whereas strict will screen for well-defined clusters such as Ketosynthases.

You can see the rules for the levels of strictness here.

For more information see the antiSMASH documentation.

Modifies tool parameter(s):

  • antiSMASH: --hmmdetection-strictness

Specify which taxonomic classification of input sequence to use

type: string

This specifies which set of secondary metabolites to screen for, based on the taxon type the secondary metabolites are from.

This will run different pipelines depending on whether the input sequences are from bacteria or fungi.

For more information see the antiSMASH documentation.

Modifies tool parameter(s):

  • antiSMASH: --taxon

A deep learning genome-mining strategy for biosynthetic gene cluster prediction

Skip deepBGC during the BGC screening.

type: boolean

Path to local deepBGC database folder.

type: string

Average protein-wise DeepBGC score threshold for extracting BGC regions from Pfam sequences.

type: number
default: 0.5

The DeepBGC score threshold for extracting BGC regions from Pfam sequences based on average protein-wise value. This is a prediction score that the domain is a part of a BGC.

For more information see the DeepBGC documentation.

Modifies tool parameter(s)

  • DeepBGC: --score

Run DeepBGC's internal Prodigal step in single mode to restrict detecting genes to long contigs

type: boolean

By default DeepBGC's Prodigal runs in 'single genome' mode that requires sequence lengths to be equal or longer than 20000 characters.

However, more fragmented reads from MAGs often result in contigs shorter than this. Therefore, nf-core/funcscan will run with the meta mode by default, but providing this parameter allows to override this and run in single genome mode again.

For more information check Prodigal documentation.

Modifies tool parameter(s)

  • DeepBGC: --prodigal-meta-mode

Merge detected BGCs within given number of proteins.

type: integer

Merge detected BGCs within given number of proteins.

For more information see the DeepBGC documentation.

Modifies tool parameter(s)

  • DeepBGC: --merge-max-protein-gap

Merge detected BGCs within given number of nucleotides.

type: integer

Merge detected BGCs within given number of proteins.

For more information see the DeepBGC documentation.

Modifies tool parameter(s)

  • DeepBGC: --merge-max-nucl-gap

Minimum BGC nucleotide length.

type: integer
default: 1

Minimum length a BGC must have (in bp) to be reported as detected.

For more information see the DeepBGC documentation.

Modifies tool parameter(s)

  • DeepBGC: --min-nucl

Minimum number of proteins in a BGC.

type: integer
default: 1

Minimum number of proteins in a BGC must have to be reported as 'detected'.

For more information see the DeepBGC documentation.

Modifies tool parameter(s)

  • DeepBGC: --min-proteins

Minimum number of protein domains in a BGC.

type: integer
default: 1

Minimum number of domains a BGC must have to be reported as 'detected'.

For more information see the DeepBGC documentation.

Modifies tool parameter(s)

  • DeepBGC: --min-domains

Minimum number of known biosynthetic (as defined by antiSMASH) protein domains in a BGC.

type: integer

Minimum number of biosynthetic protein domains a BGC must have to be reported as 'detected'. This is based on antiSMASH definitions.

For more information see the DeepBGC documentation.

Modifies tool parameter(s)

  • DeepBGC: --min-bio-domains

DeepBGC classification score threshold for assigning classes to BGCs.

type: number
default: 0.5

DeepBGC classification score threshold for assigning classes to BGCs.

For more information see the DeepBGC documentation.

Modifies tool parameter(s)

  • DeepBGC: --classifier-score

Biosynthetic gene cluster detection

Skip GECCO during the BGC screening.

type: boolean

Enable unknown region masking to prevent genes from stretching across unknown nucleotides.

type: boolean

Enable unknown region masking to prevent genes from stretching across unknown nucleotides during ORF detection based on P(y)rodigal.

For more information see the GECCO documentation.

Modifies tool parameter(s):

  • GECCO: --mask

The minimum number of coding sequences a valid cluster must contain.

type: integer
default: 3

Specify the number of consecutive genes a hit must have to be considered a part of a possible BGC region during BGC extraction.

For more information see the GECCO documentation.

Modifies tool parameter(s):

  • GECCO: --cds

The p-value cutoff for protein domains to be included.

type: number
default: 1e-9

The p-value cutoff for protein domains to be included.

For more information see the GECCO documentation.

Modifies tool parameter(s):

  • GECCO: --pfilter

The probability threshold for cluster detection.

type: number
default: 0.8

Specify the minimum probability a predicted gene must have to be considered a part of a BGC during BGC extraction.

Reducing this value may increase number and length of hits, but will reduce the accuracy of the predictions.

For more information see the GECCO documentation.

Modifies tool parameter(s):

  • GECCO: --threshold

The minimum number of annotated genes that must separate a cluster from the edge.

type: integer

The minimum number of annotated genes that must separate a possible BGC cluster from the edge. Edge clusters will still be included if they are longer. A lower number will increase the number of false positives on small contigs. Used during BGC extraction.

For more information see the GECCO documentation.

Modifies tool parameter(s):

  • GECCO: --edge-distance

Biosynthetic Gene Cluster detection based on predefined HMM models

Skip HMMsearch during BGC-screening.

type: boolean

Specify path to the BGC hmm model file(s) to search against. Must have quotes if wildcard used.

type: string

HMMSearch performs biosequence analysis using profile hidden Markov Models.
The models are specified in.hmm files that are specified with this parameter

e.g.

--bgc_hmmsearch_models '/<path>/<to>/<models>/*.hmm'  

You must wrap the path in quotes if you use a wildcard, to ensure Nextflow expansion not bash!

For more information check HMMER documentation.

Saves a multiple alignment of all significant hits to a file.

type: boolean

Save a multiple alignment of all significant hits (those satisfying inclusion thresholds) to a file

For more information check HMMER documentation.

Modifies tool parameter(s):

  • HMMsearch: -A

Save a simple tabular file summarising the per-target output.

type: boolean

Save a simple tabular (space-delimited) file summarizing the per-target output, with one data line per homologous target sequence found.

For more information check HMMER documentation.

Modifies tool parameter(s)

  • HMMsearch: --tblout

Save a simple tabular file summarising the per-domain output.

type: boolean

Save a simple tabular (space-delimited) file summarizing the per-domain output, with one data line per homologous domain detected in a query sequence for each homologous model.

For more information check HMMER documentation.

Modifies tool parameter(s)

  • HMMsearch:--domtblout

Influences parameters required for the reporting workflow.

Specifies summary output format

type: string

Specifies which summary report format to generate with hamronize summarize: tsv, json or interactive (html)

Modifies tool parameter(s)

  • HMMsearch: -t, --summary_type

Reference genome related files and options required for the workflow.

Name of iGenomes reference.

hidden
type: string

If using a reference genome configured in the pipeline using iGenomes, use this parameter to give the ID for the reference. This is then used to build the full paths for all required reference genome files e.g. --genome GRCh38.

See the nf-core website docs for more details.

Path to FASTA genome file.

hidden
type: string
pattern: ^\S+\.fn?a(sta)?(\.gz)?$

This parameter is mandatory if --genome is not specified. If you don't have a BWA index available this will be generated for you automatically. Combine with --save_reference to save BWA index for future runs.

Do not load the iGenomes reference config.

hidden
type: boolean

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.

Parameters used to describe centralised config profiles. These should not be edited.

Git commit id for Institutional configs.

hidden
type: string
default: master

Base directory for Institutional configs.

hidden
type: string
default: https://raw.githubusercontent.com/nf-core/configs/master

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 this parameter.

Institutional config name.

hidden
type: string

Institutional config description.

hidden
type: string

Institutional config contact information.

hidden
type: string

Institutional config URL link.

hidden
type: string

Set the top limit for requested resources for any single job.

Maximum number of CPUs that can be requested for any single job.

hidden
type: integer
default: 16

Use 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.

hidden
type: string
default: 128.GB
pattern: ^\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.

hidden
type: string
default: 240.h
pattern: ^(\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.

hidden
type: boolean

Display version and exit.

hidden
type: boolean

Method used to save pipeline results to output directory.

hidden
type: string

The 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.

Email address for completion summary, only when pipeline fails.

hidden
type: string
pattern: ^([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.

hidden
type: boolean

File size limit when attaching MultiQC reports to summary emails.

hidden
type: string
default: 25.MB
pattern: ^\d+(\.\d+)?\.?\s*(K|M|G|T)?B$

Do not use coloured log outputs.

hidden
type: boolean

Incoming hook URL for messaging service

hidden
type: string

Incoming hook URL for messaging service. Currently, MS Teams and Slack are supported.

Custom config file to supply to MultiQC.

hidden
type: string

Custom logo file to supply to MultiQC. File name must also be set in the MultiQC config file

hidden
type: string

Custom MultiQC yaml file containing HTML including a methods description.

type: string

Boolean whether to validate parameters against the schema at runtime

hidden
type: boolean
default: true

Show all params when using --help

hidden
type: boolean

By 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.

hidden
type: boolean

By default, when an unrecognised parameter is found, it returns a warinig.

Validation of parameters in lenient more.

hidden
type: boolean

Allows string values that are parseable as numbers or booleans. For further information see JSONSchema docs.