### Example params.yaml for nf-core/funcscan

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

A sample YAML file demonstrating how to specify pipeline parameters like input and output directories.

```yaml
input: './samplesheet.csv'
outdir: './results/'
<...>
```

--------------------------------

### Run nf-core/funcscan with Specific Tool Skipping

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Example command to run AMP and ARG screening while skipping specific tools within those workflows.

```bash
nextflow run nf-core/funcscan --input samplesheet.csv --outdir <OUTDIR> -profile docker --run_arg_screening --arg_skip_deeparg --run_amp_screening --amg_skip_macrel
```

--------------------------------

### Download and Install Bakta Database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Installs Bakta via conda and downloads the full or light database. Ensure the database is untarred after download.

```bash
conda create -n bakta -c bioconda bakta
conda activate bakta

bakta_db download --output <LOCATION_TO_STORE> --type <full|light>
```

```bash
tar xvzf db.tar.gz
```

--------------------------------

### Install and activate MMSeqs2

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Install MMSeqs2 using conda and activate the environment. This is required for downloading MMSeqs2 databases.

```bash
conda create -n mmseqs2 -c bioconda mmseqs2
conda activate mmseqs2
```

--------------------------------

### Install and activate DeepARG

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Install DeepARG using conda and activate the environment. This is a prerequisite for downloading the database.

```bash
conda create -n deeparg -c bioconda deeparg
conda activate deeparg
```

--------------------------------

### Install and Activate antiSMASH Environment

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Create and activate a conda environment for antiSMASH to ensure database compatibility. This is a prerequisite for supplying antiSMASH databases to the pipeline.

```bash
conda create -n antismash -c bioconda antismash
```

```bash
conda activate antismash
```

--------------------------------

### Install and activate AMRFinderPlus

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Install AMRFinderPlus version 3.12.8 using conda and activate the environment. This is a prerequisite for updating the database.

```bash
conda create -n amrfinderplus -c bioconda ncbi-amrfinderplus=3.12.8
conda activate amrfinderplus
```

--------------------------------

### Example Samplesheet Format

Source: https://github.com/nf-core/funcscan/blob/main/README.md

Defines the structure for the input samplesheet, mapping sample identifiers to fasta files. Ensure each row represents a fasta file of assembled contig sequences.

```csv
sample,fasta
CONTROL_REP1,AEG588A1_001.fasta
CONTROL_REP2,AEG588A1_002.fasta
CONTROL_REP3,AEG588A1_003.fasta
```

--------------------------------

### Run Basic nf-core/funcscan Pipeline

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

This is the typical command to launch the pipeline with the docker profile and enable one or more screening workflows.

```bash
nextflow run nf-core/funcscan --input samplesheet.csv --outdir <OUTDIR> -profile docker --run_<amp/arg/bgc>_screening
```

--------------------------------

### Set up ABRicate Conda Environment

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Create and activate a Conda environment for ABRicate. This is necessary before using ABRicate with custom databases.

```bash
## Create conda environment
conda create -n abricate -c bioconda abricate
conda activate abricate
```

--------------------------------

### Configure Bakta Database Path

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Specify the path to the pre-downloaded and untarred Bakta database using the --annotation_bakta_db flag.

```bash
--annotation_bakta_db /<path>/<to>/<db>/
```

--------------------------------

### Run nf-core/funcscan with Params File

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Execute the pipeline using a YAML parameters file for configuration, ensuring not to use `-c` for pipeline settings.

```bash
nextflow run nf-core/funcscan -profile docker -params-file params.yaml
```

--------------------------------

### Download CARD Database for RGI

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use wget to download the CARD database. This is a prerequisite for running RGI.

```bash
wget https://card.mcmaster.ca/latest/data
```

--------------------------------

### Download AMPcombi Reference Database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use this script to download the default DRAMP database for AMPcombi. Ensure you are in the desired directory before running.

```bash
mkdir -p ampcombi/amp_ref_database
cd ampcombi/
wget https://github.com/nf-core/funcscan/raw/<PIPELINE_VERSION>/bin/ampcombi_download.py
python3 ampcombi_download.py
```

--------------------------------

### Using Configuration Profiles with Nextflow

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

The '-profile' argument selects a configuration profile for different compute environments. It's highly recommended to use container profiles like 'docker' or 'singularity' for reproducibility. Multiple profiles can be combined, with later profiles overwriting earlier ones.

```bash
-profile test,docker
```

```bash
-profile docker
```

```bash
-profile singularity
```

```bash
-profile podman
```

```bash
-profile shifter
```

```bash
-profile charliecloud
```

```bash
-profile apptainer
```

```bash
-profile wave
```

```bash
-profile conda
```

--------------------------------

### Download abricate database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use the abricate-get_db command to download the bacmet2 database. The logging output will indicate the download location.

```bash
abricate-get_db --db bacmet2
```

--------------------------------

### Running the nf-core/funcscan Pipeline

Source: https://github.com/nf-core/funcscan/blob/main/README.md

Command to execute the funcscan pipeline using Nextflow. Specify the profile, input samplesheet, output directory, and enable desired screening modules.

```bash
nextflow run nf-core/funcscan \
   -profile <docker/singularity/podman/shifter/charliecloud/conda/institute> \
   --input samplesheet.csv \
   --outdir <OUTDIR> \
   --run_amp_screening \
   --run_arg_screening \
   --run_bgc_screening
```

--------------------------------

### Samplesheet with 2 Columns

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

A basic samplesheet with two columns: 'sample' for the sample name and 'fasta' for the path to the FASTA file. This is used when no pre-annotated data is provided.

```csv
sample,fasta
sample_1,/<path>/<to>/wastewater_metagenome_contigs_1.fasta.gz
sample_2,/<path>/<to>/wastewater_metagenome_contigs_2.fasta.gz
```

--------------------------------

### Specify abricate database path in pipeline

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Pass the downloaded abricate database directory and ID to the pipeline using --arg_abricate_db and --arg_abricate_db_id.

```bash
--arg_abricate_db /<path>/<to>/<abricate>/db/ --arg_abricate_db_id bacmet2
```

--------------------------------

### Download MMSeqs2 database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use the 'mmseqs databases' command to download a specified database to a chosen location. A temporary directory is also specified.

```bash
mmseqs databases <DATABASE_NAME> <LOCATION_TO_STORE> tmp/
```

--------------------------------

### Specify Configuration File

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use the `-c` flag to provide a path to a custom configuration file for your Nextflow pipeline.

```bash
nextflow run your_pipeline -c /path/to/your/custom.config
```

--------------------------------

### Specify Custom MMseqs2 Database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use this parameter to point to a custom MMseqs2 database directory. The directory must contain database files like '<dbname>.version' and '<dbname>.taxonomy'.

```bash
--taxa_classification_mmseqs_db '<path>/<to>/<mmsesqs_custom_database>/<directory>'
```

--------------------------------

### Specify Samplesheet Input

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use the --input parameter to specify the location of your samplesheet file. The samplesheet must be a CSV file with a header row.

```bash
--input '[path to samplesheet file]'
```

--------------------------------

### Download and Extract InterProScan Database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Download and extract the InterProScan database locally. This is an alternative to pipeline-managed downloads and can be time-consuming.

```bash
curl -L https://ftp.ebi.ac.uk/pub/software/unix/iprscan/5/5.72-103.0/interproscan-5.72-103.0-64-bit.tar.gz -o interproscan_db/interproscan-5.72-103.0-64-bit.tar.gz
```

```bash
tar -xzf interproscan_db/interproscan-5.72-103.0-64-bit.tar.gz -C interproscan_db/
```

--------------------------------

### Run hmmsearch for AMPs

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Enables HMM search for antimicrobial peptides (AMPs) by providing a directory containing HMM model files. Wrap the path in double quotes if using wildcards.

```bash
--amp_run_hmmsearch --amp_hmmsearch_models "/<path>/<to>/<amp>/*.hmm"
```

--------------------------------

### Run Protein Annotation with InterProScan

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Activate the protein annotation workflow using InterProScan. This flag initiates the process of scanning sequences against the InterPro database.

```bash
--run_protein_annotation
```

--------------------------------

### Specify Custom AMPcombi Database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Pass a custom AMPcombi database directory to the pipeline using this flag. The directory should contain FASTA and TSV files.

```bash
--amp_ampcombi_db '/<path>/<to>/<ampcombi_database>'
```

--------------------------------

### Run Nextflow in Background

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use the `-bg` flag to launch Nextflow in the background, detaching it from your terminal. This ensures the pipeline continues running even if you log out. Logs are saved to a file.

```bash
nextflow run your_pipeline -bg
```

--------------------------------

### Specify Pipeline Version for Reproducibility

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use the '-r' flag followed by a specific version tag (e.g., '1.3.1') to ensure a consistent pipeline version is used for runs. This is crucial for reproducibility and is logged in reports.

```bash
nextflow run nf-core/funcscan -r 1.3.1 --input samplesheet.csv
```

--------------------------------

### Specify AMRFinderPlus database path in pipeline

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Provide the path to a local AMRFinderPlus database using the --arg_amrfinderplus_db argument. Ensure the path points to the 'latest' directory containing database files.

```bash
--arg_amrfinderplus_db '/<path>/<to>/<amrfinderplus_db>/latest'
```

--------------------------------

### Extract CARD Database Archive

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Extract the downloaded CARD database archive using the tar command. This prepares the database for use with RGI.

```bash
tar -xjvf data
```

--------------------------------

### Samplesheet with 4 Columns

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

An advanced samplesheet with four columns: 'sample', 'fasta', 'protein', and 'gbk'. This format is used when providing pre-annotated protein and Genbank files, skipping pipeline annotation steps.

```csv
sample,fasta,protein,gbk
sample_1,/<path>/<to>/wastewater_metagenome_contigs_1.fasta.gz,/<path>/<to>/wastewater_metagenome_contigs_1.faa,/<path>/<to>/wastewater_metagenome_contigs_1.fasta.gbk
sample_2,/<path>/<to>/wastewater_metagenome_contigs_2.fasta.gz,/<path>/<to>/wastewater_metagenome_contigs_2.faa,/<path>/<to>/wastewater_metagenome_contigs_2.fasta.gbk
```

--------------------------------

### Update nf-core/funcscan Pipeline

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Run this command to pull the latest pipeline code from GitHub and update the cached version. This ensures you are using the most recent pipeline code for subsequent runs.

```bash
nextflow pull nf-core/funcscan
```

--------------------------------

### Download DeepARG database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use the 'deeparg download_data' command to download the DeepARG database to a specified output directory.

```bash
deeparg download_data -o /<path>/<to>/<database_location>/
```

--------------------------------

### Resume Pipeline Execution

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use the `-resume` flag to restart a pipeline from where it left off. Nextflow will reuse cached results if inputs are identical. You can also specify a run name to resume a specific execution.

```bash
# Resume pipeline with cached results
nextflow run your_pipeline -resume

# Resume a specific run by name
nextflow run your_pipeline -resume [run-name]
```

--------------------------------

### Download DeepBGC Database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Download the DeepBGC database using the deepbgc command after setting the DEEPBGC_DOWNLOADS_DIR environment variable. This is an alternative to pipeline-managed downloads.

```bash
conda create -n deepbgc -c bioconda deepbgc
```

```bash
conda activate deepbgc
```

```bash
export DEEPBGC_DOWNLOADS_DIR=<PREFERRED_CACHE_DIRECTORY>
```

```bash
deepbgc download
```

--------------------------------

### Specify DeepARG database path in pipeline

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Provide the path to the downloaded DeepARG database directory using the --arg_deeparg_db argument. Include the version number with --arg_deeparg_db_version.

```bash
--arg_deeparg_db '/<path>/<to>/<deeparg>/<db>/'
```

--------------------------------

### Update AMRFinderPlus database

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Run 'amrfinder --update' to download the latest AMRFinderPlus database to the default location. The database directory is named in a YYYY-MM-DD.version format.

```bash
amrfinder --update
```

--------------------------------

### Set Nextflow JVM Memory Options

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Limit the memory usage of the Nextflow Java Virtual Machine by setting the NXF_OPTS environment variable. This is typically added to your shell profile like ~/.bashrc.

```bash
export NXF_OPTS='-Xms1g -Xmx4g'
```

--------------------------------

### Email Structure and Logo Embedding

Source: https://github.com/nf-core/funcscan/blob/main/assets/sendmail_template.txt

Defines the basic structure of the email, including MIME version, content type, and how to embed a PNG logo using base64 encoding. The logo is read from a file and encoded.

```Groovy
To: $email
Subject: $subject
Mime-Version: 1.0
Content-Type: multipart/related;boundary="nfcoremimeboundary"

--nfcoremimeboundary
Content-Type: text/html; charset=utf-8

$email_html

--nfcoremimeboundary
Content-Type: image/png;name="nf-core-funcscan_logo.png"
Content-Transfer-Encoding: base64
Content-ID: <nfcorepipelinelogo>
Content-Disposition: inline; filename="nf-core-funcscan_logo_light.png"

<% out << new File("$projectDir/assets/nf-core-funcscan_logo_light.png").
    bytes.
    encodeBase64().
    toString().
    tokenize( '\n' )*.
    toList()*. 
    collate( 76 )*. 
    collect { it.join() }. 
    flatten(). 
    join( '\n' ) %>
```

--------------------------------

### Specify MMseqs2 Database ID

Source: https://github.com/nf-core/funcscan/blob/main/docs/usage.md

Use this parameter to specify a pre-compiled MMseqs2 database by its label. The default is 'Kalamari' for amino acid-based alignment.

```bash
--taxa_classification_mmseqs_db_id 'Kalamari'
```

--------------------------------

### Conditional MultiQC Report Embedding

Source: https://github.com/nf-core/funcscan/blob/main/assets/sendmail_template.txt

Conditionally embeds the MultiQC report into the email if the `mqcFile` is provided and its size is less than `mqcMaxSize`. The report is base64 encoded and attached.

```Groovy
<%
if (mqcFile){
def mqcFileObj = new File("$mqcFile")
if (mqcFileObj.length() < mqcMaxSize){
out << """
--nfcoremimeboundary
Content-Type: text/html; name=\"multiqc_report\"
Content-Transfer-Encoding: base64
Content-ID: <mqcreport>
Content-Disposition: attachment; filename=\"${mqcFileObj.getName()}\""

${mqcFileObj.
    bytes.
    encodeBase64().
    toString().
    tokenize( '\n' )*.
    toList()*. 
    collate( 76 )*. 
    collect { it.join() }. 
    flatten(). 
    join( '\n' )}
"""
}}
%>
```

--------------------------------

### Email Multipart Boundary End

Source: https://github.com/nf-core/funcscan/blob/main/assets/sendmail_template.txt

Marks the end of the multipart MIME message. This boundary signifies the completion of all parts within the email.

```Plain Text
--nfcoremimeboundary--
```

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