nf-core/mag

Input FastQ files (gzip compressed) or CSV samplesheet file containing information about the samples in the experiment.

Specifies that the input is single-end reads.

Additional input CSV samplesheet containing information about pre-computed assemblies. When set, both read pre-processing and assembly are skipped and the pipeline begins at the binning stage.

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

Email address for completion summary.

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

Custom MultiQC yaml file containing HTML including a methods description.

Fix number of CPUs for MEGAHIT to 1. Not increased with retries.

Fix number of CPUs used by SPAdes. Not increased with retries.

Fix number of CPUs used by SPAdes hybrid. Not increased with retries.

RNG seed for MetaBAT2.

Specify which adapter clipping tool to use.

Specify to save the resulting clipped FASTQ files to —outdir.

The minimum length of reads must have to be retained for downstream analysis.

Minimum phred quality value of a base to be qualified in fastp.

The mean quality requirement used for per read sliding window cutting by fastp.

Save reads that fail fastp filtering in a separate file. Not used downstream.

The minimum base quality for low-quality base trimming by AdapterRemoval.

Turn on quality trimming by consecutive stretch of low quality bases, rather than by window.

Forward read adapter to be trimmed by AdapterRemoval.

Reverse read adapter to be trimmed by AdapterRemoval for paired end data.

Name of iGenomes reference for host contamination removal.

Fasta reference file for host contamination removal.

Use the --very-sensitive instead of the--sensitivesetting for Bowtie 2 to map reads against the host genome.

Save the read IDs of removed host reads.

Specify to save input FASTQ files with host reads removed to —outdir.

Keep reads similar to the Illumina internal standard PhiX genome.

Skip read preprocessing using fastp or adapterremoval.

Specify to save input FASTQ files with phiX reads removed to —outdir.

Run BBnorm to normalize sequence depth.

Set BBnorm target maximum depth to this number.

Set BBnorm minimum depth to this number.

Save normalized read files to output directory.

Skip removing adapter sequences from long reads.

Discard any read which is shorter than this value.

Keep this percent of bases.

The higher the more important is read length when choosing the best reads.

Keep reads similar to the ONT internal standard Escherichia virus Lambda genome.

Specify to save input FASTQ files with lamba reads removed to —outdir.

Specify to save the resulting clipped FASTQ files to —outdir.

Specify to save the resulting length filtered FASTQ files to —outdir.

Database for taxonomic binning with centrifuge.

Database for taxonomic binning with kraken2.

Database for taxonomic binning with krona

Skip creating a krona plot for taxonomic binning.

Database for taxonomic classification of metagenome assembled genomes. Can be either a zipped file or a directory containing the extracted output of such.

Generate CAT database.

Save the CAT database generated when specified by --cat_db_generate.

Only return official taxonomic ranks (Kingdom, Phylum, etc.) when running CAT.

Skip the running of GTDB, as well as the automatic download of the database

Specify the location of a GTDBTK database. Can be either an uncompressed directory or a .tar.gz archive. If not specified will be downloaded for you when GTDBTK or binning QC is not skipped.

Specify the location of a GTDBTK mash database. If missing, GTDB-Tk will skip the ani_screening step

Min. bin completeness (in %) required to apply GTDB-tk classification.

Max. bin contamination (in %) allowed to apply GTDB-tk classification.

Min. fraction of AA (in %) in the MSA for bins to be kept.

Min. alignment fraction to consider closest genome.

Number of CPUs used for the by GTDB-Tk run tool pplacer.

Reduce GTDB-Tk memory consumption by running pplacer in a setting writing to disk.

Database for virus classification with geNomad

Co-assemble samples within one group, instead of assembling each sample separately.

Additional custom options for SPAdes.

Additional custom options for MEGAHIT.

Skip Illumina-only SPAdes assembly.

Skip SPAdes hybrid assembly.

Skip MEGAHIT assembly.

Skip metaQUAST.

Skip Prodigal gene prediction

Skip Prokka genome annotation.

Skip MetaEuk gene prediction and annotation

A string containing the name of one of the databases listed in the mmseqs2 documentation. This database will be downloaded and formatted for eukaryotic genome annotation. Incompatible with —metaeuk_db.

Path to either a local fasta file of protein sequences, or to a directory containing an mmseqs2-formatted database, for annotation of eukaryotic genomes.

Save the downloaded mmseqs2 database specified in --metaeuk_mmseqs_db.

Run virus identification.

Minimum geNomad score for a sequence to be considered viral

Number of groups that geNomad’s MMSeqs2 databse should be split into (reduced memory requirements)

Defines mapping strategy to compute co-abundances for binning, i.e. which samples will be mapped against the assembly.

Skip metagenome binning entirely

Skip MetaBAT2 Binning

Skip MaxBin2 Binning

Skip CONCOCT Binning

Minimum contig size to be considered for binning and for bin quality check.

Minimal length of contigs that are not part of any bin but treated as individual genome.

Maximal number of contigs that are not part of any bin but treated as individual genome.

Bowtie2 alignment mode

Save the output of mapping raw reads back to assembled contigs

Enable domain-level (prokaryote or eukaryote) classification of bins using Tiara. Processes which are domain-specific will then only receive bins matching the domain requirement.

Minimum contig length for Tiara to use for domain classification. For accurate classification, should be longer than 3000 bp.

Disable bin QC with BUSCO or CheckM.

Specify which tool for bin quality-control validation to use.

Download URL for BUSCO lineage dataset, or path to a tar.gz archive, or local directory containing already downloaded and unpacked lineage datasets.

Run BUSCO with automated lineage selection, but ignoring eukaryotes (saves runtime).

Save the used BUSCO lineage datasets provided via --busco_db.

Enable clean-up of temporary files created during BUSCO runs.

Path to local folder containing already downloaded and uncompressed CheckM database.

Save the used CheckM reference files downloaded when not using —checkm_db parameter.

Turn on bin refinement using DAS Tool.

Specify single-copy gene score threshold for bin refinement.

Specify which binning output is sent for downstream annotation, taxonomic classification, bin quality control etc.

Turn on GUNC genome chimerism checks

Specify a path to a pre-downloaded GUNC dmnd database file

Specify which database to auto-download if not supplying own

Save the used GUNC reference files downloaded when not using —gunc_db parameter.

Turn on/off the ancient DNA subworfklow

PyDamage accuracy threshold

deactivate damage correction of ancient contigs using variant and consensus calling

Ploidy for variant calling

minimum base quality required for variant calling

minimum minor allele frequency for considering variants

minimum genotype quality for considering a variant high quality

minimum genotype quality for considering a variant medium quality

minimum number of bases supporting the alternative allele