Viralgenie pipeline parameters

A pipeline to reconstruct consensus genomes and identify intrahost variants from metagenomic sequencing data or enriched based sequencing data like hybrid capture.

Input/output options

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

Parameter	Description	Default
input	Path to comma-separated file containing information about the samples in the experiment. Help 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 comma-separated file with 3 columns, and a header row. See usage docs.
outdir	The output directory where the results will be saved. You have to use absolute paths to storage on Cloud infrastructure.
metadata	Sample metadata that is included in the multiqc report
email	Email address for completion summary. Help 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.

Preprocessing options

Options related to the trimming, low complexity and host removal steps of the reads

Parameter	Description	Default
skip_preprocessing	Skip read preprocessing and use input reads for downstream analysis
skip_fastqc	Skip read quality statistics summary tool 'fastqc'
save_final_reads	Save reads after the final preprocessing step	True
save_intermediate_reads	Save reads after every preprocessing step
with_umi	With or without umi detection
skip_umi_extract	With or without umi extraction	True
umi_deduplicate	Specify at what level UMI deduplication should occur.	read
humid_mismatches	Specify the maximum number of mismatches between reads for them to still be considered neighbors.	1
humid_strategy	Specify the strategy for umi-deduplication directional vs cluster	directional
umitools_dedup_strategy	Specify the strategy or method for umi-tools deduplication on mapping level	directional
umi_discard_read	Discard R1 / R2 if required 0, meaning not to discard	0
trim_tool	The used trimming tool	fastp
skip_trimming	Skip read trimming
fastp_deduplicate	Use Fastp's deduplicate option
fastp_dedup_accuracy	Define the accuracy used for hashes while deduplicating with faspt
adapter_fasta	Fasta file of adapters
save_trimmed_fail	Specify true to save files that failed to pass trimming thresholds ending in *.fail.fastq.gz
save_merged	Specify true to save all merged reads to the a file ending in *.merged.fastq.gz
min_trimmed_reads	Inputs with fewer than this reads will be filtered out of the "reads" output channel	1
skip_complexity_filtering	Skip filtering of low complexity regions in reads Help Low-complexity sequences are defined as having commonly found stretches of nucleotides with limited information content (e.g. the dinucleotide repeat CACACACACA). Such sequences can produce a large number of high-scoring but biologically insignificant results in database searches	True
contaminants	Reference files containing adapter and/or contaminant sequences for sequence kmer matching (used by bbduk)
skip_hostremoval	Skip the removal of host read sequences
host_k2_db	Kraken2 database used to remove host and conamination	s3://ngi-igenomes/test-data/viralrecon/kraken2_human.tar.gz
host_k2_library	Kraken2 library(s) required to remove host and contamination Help Only used when no host kraken2 database is specified.	human
skip_host_fastqc	Skip the fastqc step after host & contaminants were removed

Metagenomic diveristy

Parameters used to determine the metagenomic diversity of the sample

Parameter	Description	Default
skip_read_classification	Skip determining the metagenomic diversity of the sample
read_classifiers	Specify the taxonomic read classifiers, choices are 'kaiju,kraken2'	kraken2,kaiju
save_databases	Save the used databases
kraken2_db	Location of the Kraken2 database	https://genome-idx.s3.amazonaws.com/kraken/k2_viral_20230314.tar.gz
kraken2_save_reads	Save classified and unclassified reads as fastq files
kraken2_save_readclassification	Save summary overview of read classifications in a txt file
kraken2_save_minimizers	Save kraken2's used minimizers
bracken_db	Location of bracken database	https://genome-idx.s3.amazonaws.com/kraken/k2_viral_20230314.tar.gz
kaiju_db	Location of Kaiju database	https://kaiju-idx.s3.eu-central-1.amazonaws.com/2023/kaiju_db_rvdb_2023-05-26.tgz
kaiju_taxon_rank	Level of taxa rank that needs to be determined	species

Assembly

Parameters relating to the used assembly methods

Parameter	Description	Default
skip_assembly	Skip de novo assembly of reads
assemblers	The specified tools for denovo assembly, multiple options are possible	spades,trinity,megahit
spades_mode	specific SPAdes mode to run	rnaviral
spades_hmm	File or directory with amino acid HMMs for Spades HMM-guided mode.
spades_yml	Path to yml file containing read information. Help The raw FASTQ files listed in this YAML file MUST be supplied to the respective illumina/pacbio/nanopore input channel(s) in addition to this YML. File entries in this yml must contain only the file name and no paths.
assembler_patterns	Regex pattern to identify contigs that have been made by the assemblers

Polishing

Parameters relating to the refinement of denovo contigs

Parameter	Description	Default
skip_polishing	Skip the refinement/polishing of contigs through reference based scaffolding and read mapping
save_intermediate_polishing	Save intermediate polishing files Help There are multiple processes within the polishing subworkflow that might not contain relevant information
reference_pool	Set of fasta sequences used as potential references for the contigs	https://rvdb.dbi.udel.edu/download/C-RVDBvCurrent.fasta.gz
skip_precluster	Skip the preclustering of assemblies to facilitate downstream processing of assemblies
keep_unclassified	Keep the contigs that could not be classified with the taxonomic databases (kaiju_db & kraken2_db) Help Within the preclustering step, all contigs will get a taxonomic classification using the provided databases for the metagenomic tools. In some cases, the number of unclassified contigs, can be very large if the database is restrictive. This will result in large clusters in downstream processing that can take up a lot of resources despite not being a priority in some analyses. So set it to True if you want to keep unclassified contigs and set it to False if you don't want to keep them.	True
precluster_classifiers	Specify the metagenomic classifiers to use for contig taxonomy classification: 'kraken2,kaiju'	kraken2,kaiju
precluster_merge_strategy	Taxon conflict resolution mode, must be 1 (Kaiju), 2 (Kraken), lca, or lowest. Help The option -c determines the method of resolving conflicts in the taxonomic assignment for a read. Possible values are '1', '2', 'lca', 'lowest': '1' -> the taxon id from Kaiju is used. '2' -> the taxon id from Kraken is used. 'lca' -> the least common ancestor of the two taxon ids from both input files is used. 'lowest' -> the lower rank of the two taxa is used if they are within the same lineage. Otherwise the LCA is used.	lca
precluster_simplification_level	Level of taxonomic simplification Help The taxonomic classification of the contigs can be simplified to a certain level. This can be done by specifying the taxonomic rank to which the classification should be simplified.
precluster_exclude_taxa	Hard constrain for taxa to exclude from the preclustering, if multiple given make sure to enclose with '"' and separate with a space. Help The taxonomic classification of the contigs can be filtered. This can be done by specifying a list of taxa that should be excluded from the results.
precluster_exclude_children	Taxon ids to exclude along with all their children from the preclustering, if multiple given make sure to enclose with '"' and separate with a space. Help The taxonomic classification of the contigs can be filtered. This can be done by specifying a list of taxa that should be excluded along with all their children from the results.
precluster_exclude_parents	Taxon ids to exclude along with all their parents from the preclustering, if multiple given make sure to enclose with '"' and separate with a space. Help The taxonomic classification of the contigs can be filtered. This can be done by specifying a list of taxa that should be excluded along with all their parents from the results.
precluster_include_children	Taxon ids to include along with all their children from the preclustering, if multiple given make sure to enclose with '"' and separate with a space. Help The taxonomic classification of the contigs can be filtered. This can be done by specifying a list of taxa that should be included along with all their children from the results.
precluster_include_parents	Taxon ids to include along with all their parents from the preclustering, if multiple given make sure to enclose with '"' and separate with a space. Help The taxonomic classification of the contigs can be filtered. This can be done by specifying a list of taxa that should be included along with all their parents from the results.
cluster_method	Cluster algorithm used for contigs	mash
network_clustering	(only with mash) Algorithm to partition the network. Help Mash creates a distance matrix that gets translated into a network of connectected nodes where the edges represent the similarity. This network is then split up using the specified method. - leiden algorithm: a hierarchical clustering algorithm, that recursively merges communities into single nodes by greedily optimizing the modularity - [connected_components] algorithm: a clustering algorithm that defines the largest possible communities where each node within a subset is reachable from every other node in the same subset via any edge .	connected_components
skip_hybrid_consensus	Skip creation of the hybrid consensus, instead keep the scaffold with ambiguous bases if the depth of scaffolds is not high enough.
identity_threshold	Identity threshold value used in clustering algorithms	0.6
min_contig_size	Minimum allowed contig size Help Setting this to a low value will result in a large number of questionable contigs and an increase in computation time	500
max_contig_size	Maximum allowed contig size	10000000
max_n_perc	Define the maximum percentage of ambiguous bases in a contig	50
skip_singleton_filtering	Skip the filtering of contigs that did not cluster together with other contigs Help Setting this to true will cause the pipeline not to remove contigs that don't have similar contigs. Filtering settings can be further specified with min_contig_size and max_n_100kbp.

Iterative consensus refinement

Define parameters for iterations to update denovo consensus using reference based improvements

Parameter	Description	Default
skip_iterative_refinement	Don't realign reads to consensus sequences and redefine the consensus through (multiple) iterations
iterative_refinement_cycles	number of iterations	2
intermediate_mapper	mapping tool used during iterations	bwamem2
intermediate_variant_caller	variant caller used during iterations	ivar
call_intermediate_variants	call variants during the iterations Help Will always be done when iterative consensus caller is bcftools
intermediate_consensus_caller	consensus tool used for calling new consensus during iterations	bcftools
intermediate_mapping_stats	calculate summary statistics during iterations	True

Variant analysis

Parameters relating to the analysis of variants associated to contigs and scaffolds

Parameter	Description	Default
skip_variant_calling	Skip the analysis of variants for the external reference or contigs
mapper	Define which mapping tool needs to be used when mapping reads to reference	bwamem2
mapping_constrains	Sequence to use as a mapping reference instead of the de novo contigs or scaffolds
deduplicate	deduplicate the reads Help If used with umi's, umi tools will be used to group and call consensus of each indiual read group. If not used with umi's use PicardsMarkDuplicates.	True
variant_caller	Define the variant caller to use: 'ivar' or 'bcftools'	ivar
consensus_caller	consensus tool used for calling new consensus in final iteration	ivar
umi_separator	UMI seperator in fastq header. Help If you have used an alternative method which does not separate the read id and UMI with a “_”, such as bcl2fastq which uses “:”, you can specify the separator with the option --umi_separator=, replacing with e.g “:”.	:
mash_sketch_size	Specify the sketch size, the number of (non-redundant) min-hashes that are kept. Help Larger sketches will better represent the sequence, but at the cost of larger sketch files and longer comparison times.	4000
mash_sketch_kmer_size	Specify the kmer size for mash to create their hashes Help larger k-mers will provide more specificity, while smaller k-mers will provide more sensitivity. Larger genomes will also require larger k-mers to avoid k-mers that are shared by chance	15
min_mapped_reads	Define the minimum number of mapped reads in order to continue the variant and consensus calling	200
mapping_stats	calculate summary statistics in final iteration	True
multiqc_comment_headers	Directory containing the mutliqc headers for multiple tables like 'clusters_summary_mqc.txt', 'blast_mqc.txt', ...	${projectDir}/assets/mqc_comment
ivar_header

Consensus QC

Apply different quality control techniques on the generated consensus genomes

Parameter	Description	Default
skip_consensus_qc	Skip the quality measurements on consensus genomes
skip_checkv	Skip the use of checkv for quality check
checkv_db	Reference database used by checkv for consensus quality control Help If not given, the most recent one is downloaded.
skip_annotation	Skip the annotation of the consensus constructs
annotation_db	Database used for annotation of the cosensus constructs Help The metada fields are stored in the fasta comment as key1:"value1"|key2:"value2"|... see docs/databases.md for more information.	https://viralzone.expasy.org/resources/Virosaurus/2020%5F4/virosaurus90%5Fvertebrate-20200330.fas.gz
skip_quast	Skip the use of QUAST for quality check
skip_blast_qc	Skip the blast search of contigs to the provided reference DB
skip_alignment_qc	Skip creating an alignment of each the collapsed clusters and each iterative step
mmseqs_searchtype	Specify the search algorithm to use for mmseqs. 0: auto 1: amino acid, 2: translated, 3: nucleotide, 4: translated nucleotide alignment Help Only search-type 3 supports both forward and reverse search 1 - BLASTP; 2 - TBLASTN; 3 - BLASTN; 4 - TBLASTX	4

Institutional config options

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

Parameter	Description	Default
custom_config_version	Git commit id for Institutional configs.	master
custom_config_base	Base directory for Institutional configs. Help 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.	https://raw.githubusercontent.com/nf-core/configs/master
config_profile_name	Institutional config name.
config_profile_description	Institutional config description.
config_profile_contact	Institutional config contact information.
config_profile_url	Institutional config URL link.

Max job request options

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

Parameter	Description	Default
max_cpus	Maximum number of CPUs that can be requested for any single job. Help Use to set an upper-limit for the CPU requirement for each process. Should be an integer e.g. --max_cpus 1	16
max_memory	Maximum amount of memory that can be requested for any single job. Help 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'	128.GB
max_time	Maximum amount of time that can be requested for any single job. Help 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'	240.h

Generic options

Less common options for the pipeline, typically set in a config file.

Parameter	Description	Default
help	Display help text.
version	Display version and exit.
publish_dir_mode	Method used to save pipeline results to output directory. Help 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.	copy
email_on_fail	Email address for completion summary, only when pipeline fails. Help An email address to send a summary email to when the pipeline is completed - ONLY sent if the pipeline does not exit successfully.
plaintext_email	Send plain-text email instead of HTML.
max_multiqc_email_size	File size limit when attaching MultiQC reports to summary emails.	25.MB
monochrome_logs	Do not use coloured log outputs.
hook_url	Incoming hook URL for messaging service Help Incoming hook URL for messaging service. Currently, MS Teams and Slack are supported.
multiqc_title	MultiQC report title. Printed as page header, used for filename if not otherwise specified.
multiqc_config	Custom config file to supply to MultiQC.
multiqc_logo	Custom logo file to supply to MultiQC. File name must also be set in the MultiQC config file
multiqc_methods_description	Custom MultiQC yaml file containing HTML including a methods description.
clean_output_on_error	Delete the output directory if the pipeline fails
custom_table_headers	Custom yaml file contian g the table column names selection and new names.	${projectDir}/assets/custom_table_headers.yml
validate_params	Boolean whether to validate parameters against the schema at runtime	True
validationShowHiddenParams	Show all params when using --help Help 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.
validationFailUnrecognisedParams	Validation of parameters fails when an unrecognised parameter is found. Help By default, when an unrecognised parameter is found, it returns a warinig.
validationSchemaIgnoreParams		global_prefix
validationLenientMode	Validation of parameters in lenient more. Help Allows string values that are parseable as numbers or booleans. For further information see JSONSchema docs.
prefix	Prefix of all output files followed by [date][pipelineversion][runName] Help Use '--global_prefix' to not have metadata embedded.
global_prefix	Global prefix set if you don't want metadata embedded in the prefix