### Pixi Installation and Usage

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/installation.md

Steps to install pixi, clone the repository, install the locked environment, and activate the shell.

```bash
# install pixi once (see https://pixi.sh/latest/#installation for alternatives)
curl -fsSL https://pixi.sh/install.sh | bash

# clone the repo and install the locked environment
git clone https://github.com/nextgenusfs/funannotate2.git
cd funannotate2
pixi install --locked

# activate the environment
pixi shell

# set the database location and install databases
export FUNANNOTATE2_DB=/path/to/funannotate2-db
funannotate2 install -d all
```

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

### Show currently installed databases

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/install.md

Command to display a list of databases that are currently installed, including their versions and installation dates.

```bash
funannotate2 install -s
```

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

### Install all databases

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/install.md

Command to download and install all required databases for funannotate2.

```bash
funannotate2 install -d all
```

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

### Install Sphinx and Theme

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/README.md

Installs the necessary packages for building the documentation.

```bash
pip install sphinx sphinx_rtd_theme
```

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

### Install development version from GitHub

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/installation.md

Command to install the development version of Funannotate2 directly from its GitHub repository.

```bash
pip install git+https://github.com/nextgenusfs/funannotate2.git
```

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

### Verify Funannotate2 Installation

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/installation.md

Command to check if Funannotate2 has been installed correctly by displaying its version.

```bash
funannotate2 --version
```

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

### Docker Installation and Usage

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/installation.md

Commands to pull the Docker image, perform sanity checks, and run a prediction job.

```bash
# pull the latest image (~8 GB; databases are baked in)
docker pull nextgenusfs/funannotate2:latest

# sanity checks
docker run --rm nextgenusfs/funannotate2:latest funannotate2 --version
docker run --rm nextgenusfs/funannotate2:latest funannotate2 install -s

# run against a local data directory, persisting the BUSCO cache across runs
mkdir -p $PWD/data $PWD/busco_cache
docker run --rm -it \
    -v $PWD/data:/data \
    -v $PWD/busco_cache:/opt/busco_cache \
    -e BUSCO_DOWNLOAD_PATH=/opt/busco_cache \
    nextgenusfs/funannotate2:latest \
    funannotate2 predict -i /data/genome.fa -o /data/out --species "My species"
```

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

### Pixi Installation

Source: https://github.com/nextgenusfs/funannotate2/blob/main/README.md

Instructions for installing pixi and then cloning and installing the funannotate2 environment using pixi.

```shell
# install pixi once (see https://pixi.sh/latest/#installation)
curl -fsSL https://pixi.sh/install.sh | bash

# clone and install the locked environment
git clone https://github.com/nextgenusfs/funannotate2.git
cd funannotate2
pixi install --locked

# activate and install databases
pixi shell
export FUNANNOTATE2_DB=/path/to/funannotate2-db
funannotate2 install -d all
```

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

### Install latest release version using pip

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/installation.md

Command to install the latest stable release of Funannotate2 using pip.

```bash
pip install funannotate2
```

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

### Conda/Mamba Installation (Linux)

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/installation.md

Commands to create a conda environment, activate it, and install Funannotate2 via pip.

```bash
mamba create -n funannotate2 gfftk gapmm2 minimap2 miniprot snap "augustus==3.5.0" glimmerhmm diamond trnascan-se table2asn gb-io buscolite
conda activate funannotate2
python -m pip install git+https://github.com/nextgenusfs/funannotate2.git
```

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

### Update all installed databases

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/install.md

Command to check for and download updates for all installed databases.

```bash
funannotate2 install -d all -u
```

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

### Reactivate environment and install remaining Python dependencies

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/installation.md

This snippet shows how to reactivate the conda environment and install Python dependencies using pip, including the funannotate2 package from GitHub.

```bash
conda activate funannotate2
python -m pip install buscolite git+https://github.com/nextgenusfs/funannotate2.git
```

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

### Set FUNANNOTATE2_DB environment variable (bash/zsh)

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/install.md

Example of how to set the FUNANNOTATE2_DB environment variable for bash or zsh shells.

```bash
# For bash/zsh
export FUNANNOTATE2_DB=/path/to/database/directory
```

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

### Example Usage: Basic cleaning with default parameters

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/clean.md

Example of basic cleaning with default parameters.

```bash
funannotate2 clean -f raw_genome.fasta -o cleaned_genome.fasta
```

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

### Installing test dependencies

Source: https://github.com/nextgenusfs/funannotate2/blob/main/tests/README.md

Commands to install necessary packages for running and testing funannotate2.

```bash
pip install pytest pytest-cov
```

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

### Apple Silicon (M series) Installation - Step 1: Install Dependencies

Source: https://github.com/nextgenusfs/funannotate2/blob/main/README.md

Installs most of the dependencies for Apple Silicon using mamba, excluding buscolite and funannotate2.

```shell
# first install most of the dependencies
mamba create -n funannotate2 --platform osx-64 "python>=3.7,<3.13" gfftk gapmm2 minimap2 miniprot snap glimmerhmm diamond trnascan-se gb-io pyhmmer pyfastx requests json-repair pytantan "mkl<2022"

# we can then add the required FUNANNOTATE2_DB env variable to the conda environment, note need to reactivate to use it
conda activate funannotate2
conda env config vars set FUNANNOTATE2_DB=/path/to/funannotate2-db
conda env config vars set AUGUSTUS_CONFIG_PATH=/path/to/augustus-3.5.0/config
conda deactivate

# now reactivate environment, and install the remaining python dependencies with pip
conda activate funannotate2
python -m pip install buscolite git+https://github.com/nextgenusfs/funannotate2.git
```

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

### Training Ab Initio Gene Predictors Example

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/usage.md

Example command to train ab initio gene prediction algorithms with Funannotate2.

```bash
funannotate2 train -f cleaned_genome.fasta -s "Aspergillus nidulans" -o anid_f2
```

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

### Set FUNANNOTATE2_DB environment variable (csh/tcsh)

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/install.md

Example of how to set the FUNANNOTATE2_DB environment variable for csh or tcsh shells.

```bash
# For csh/tcsh
setenv FUNANNOTATE2_DB /path/to/database/directory
```

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

### Conda/Mamba Installation (macOS)

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/installation.md

Commands to create a conda environment with specific platforms and Python version, set environment variables, and then install remaining dependencies with pip.

```bash
# first install most of the dependencies
mamba create -n funannotate2 --platform osx-64 "python>=3.7,<3.13" gfftk gapmm2 minimap2 miniprot snap glimmerhmm diamond trnascan-se gb-io pyhmmer pyfastx requests json-repair "mkl<2022" pytantan

# we can then add the required FUNANNOTATE2_DB env variable to the conda environment, note need to reactivate to use it
conda activate funannotate2
conda env config vars set FUNANNOTATE2_DB=/path/to/funannotate2-db
conda env config vars set AUGUSTUS_CONFIG_PATH=/path/to/augustus-3.5.0/config
conda deactivate
```

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

### Install funannotate2 in development mode

Source: https://github.com/nextgenusfs/funannotate2/blob/main/README.md

Installs the package in editable mode, useful for development.

```shell
pip install -e .
```

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

### Docker Quick Start

Source: https://github.com/nextgenusfs/funannotate2/blob/main/README.md

Instructions for pulling the latest Docker image, performing a quick sanity check, and running the prediction command.

```shell
# pull the latest image (~8 GB; databases are baked in)
docker pull nextgenusfs/funannotate2:latest
# or from GHCR
docker pull ghcr.io/nextgenusfs/funannotate2:latest

# quick sanity check
docker run --rm nextgenusfs/funannotate2:latest funannotate2 --version
docker run --rm nextgenusfs/funannotate2:latest funannotate2 install -s

# run against a local data directory, persisting the BUSCO cache across runs
mkdir -p $PWD/data $PWD/busco_cache
docker run --rm -it \
    -v $PWD/data:/data \
    -v $PWD/busco_cache:/opt/busco_cache \
    -e BUSCO_DOWNLOAD_PATH=/opt/busco_cache \
    nextgenusfs/funannotate2:latest \
    funannotate2 predict -i /data/genome.fa -o /data/out --species "My species"
```

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

### Example Usage: Cleaning with custom parameters

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/clean.md

Example of cleaning with custom parameters for minimum length, percent identity, coverage, and renaming.

```bash
funannotate2 clean -f raw_genome.fasta -o cleaned_genome.fasta -m 1000 -p 98 -c 98 -r scaffold_
```

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

### Example Workflow: Clean Genome

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/usage.md

Command to clean a genome FASTA file.

```bash
# Clean the genome
funannotate2 clean -f raw_genome.fasta -o cleaned_genome.fasta -m 1000 -r scaffold_
```

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

### Example Usage: Exhaustive cleaning

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/clean.md

Example of exhaustive cleaning to check all contigs for duplication.

```bash
funannotate2 clean -f raw_genome.fasta -o cleaned_genome.fasta --exhaustive
```

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

### Install latest code from repo

Source: https://github.com/nextgenusfs/funannotate2/blob/main/README.md

Installs the most up-to-date code from the GitHub repository, forcing an upgrade and ignoring dependencies.

```shell
python -m pip install git+https://github.com/nextgenusfs/funannotate2.git --upgrade --force --no-deps
```

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

### Example Output with Memory Monitoring Enabled

Source: https://github.com/nextgenusfs/funannotate2/blob/main/MEMORY_MONITORING.md

Illustrates the typical output seen when memory monitoring is active, showing memory estimates and usage details.

```text
Memory monitoring: using 14.4 GB limit (90% of 16.0 GB total)
Memory limit set to 16.0 GB
Memory usage estimate for 150 contigs with tools ['snap', 'augustus']:
  Total estimated peak memory: 2847.3 MB
System memory: 14.2 GB available
Processing contig scaffold_1.fasta (length: 2,847,392 bp)
SNAP memory prediction for scaffold_1.fasta: 51.4 MB
Augustus memory prediction for scaffold_1.fasta: 105.4 MB
Memory usage for snap-scaffold_1.fasta:
Process: snap-scaffold_1.fasta
Duration: 12.34 seconds
Peak RSS: 48.2 MB
Peak VMS: 156.7 MB
Average RSS: 42.1 MB
Samples collected: 247
```

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

### Running Tests

Source: https://github.com/nextgenusfs/funannotate2/blob/main/TESTING.md

Commands to install dependencies and run tests using pytest.

```bash
# Install pytest and coverage tools
pip install pytest pytest-cov

# Install funannotate2 in development mode
pip install -e .

# Run all tests
pytest

# Run with coverage report
pytest --cov=funannotate2

# Generate HTML coverage report
python scripts/run_coverage.py

# Run only unit tests
pytest tests/unit/

# Run only integration tests
pytest tests/integration/
```

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

### Force reinstallation of a specific database

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/install.md

Command to force the re-download and re-installation of a specific database, such as Pfam.

```bash
funannotate2 install -d pfam -f
```

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

### Install bleeding-edge version from GitHub

Source: https://github.com/nextgenusfs/funannotate2/blob/main/README.md

Installs the latest development version of Funannotate2 directly from its GitHub repository.

```shell
python -m pip install git+https://github.com/nextgenusfs/funannotate2.git
```

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

### Running Tests with Specific Python Versions

Source: https://github.com/nextgenusfs/funannotate2/blob/main/TESTING.md

Example of setting up a virtual environment with a specific Python version and running tests.

```bash
# Create a virtual environment with Python 3.9
python3.9 -m venv venv-py39
source venv-py39/bin/activate

# Install dependencies
pip install pytest pytest-cov
pip install -e .

# Run tests
pytest
```

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

### Load a new species

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/usage.md

Example of loading a new species into the Funannotate2 database using a .params.json file.

```bash
funannotate2 species -l new_species.params.json
```

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

### Example Workflow: Predict Genes with Trained Parameters

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/usage.md

Command to predict genes using previously trained parameters.

```bash
# Predict genes using trained parameters
funannotate2 predict -i f2_output -ps uniprot_fungi.fasta -ts rnaseq_transcripts.fasta --cpus 16
```

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

### Example Workflow: Functional Annotation

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/usage.md

Command to functionally annotate predicted genes.

```bash
# Functionally annotate genes
funannotate2 annotate -i f2_output --cpus 16
```

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

### Command Line Options for Memory Monitoring

Source: https://github.com/nextgenusfs/funannotate2/blob/main/MEMORY_MONITORING.md

Examples of how to enable, configure, and disable memory monitoring using funannotate2 predict.

```bash
# Memory monitoring is enabled by default
funannotate2 predict -i input_dir

# Set memory limit with memory monitoring (default behavior)
funannotate2 predict -i input_dir --memory-limit 16

# Disable memory monitoring if needed
funannotate2 predict -i input_dir --disable-memory-monitoring
```

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

### Example Workflow: Predict Genes with Pretrained Species

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/usage.md

Command to predict genes using pretrained species information.

```bash
# Or predict genes using pretrained species
funannotate2 predict -i f2_output -p aspergillus_fumigatus -ps uniprot_fungi.fasta -ts rnaseq_transcripts.fasta --cpus 16
```

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

### Add custom gene/product annotations

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/usage.md

Example of adding custom gene or product annotations to the funannotate2 output.

```bash
funannotate2 annotate -i f2_output --cpus 16 --curated-names custom_annotations.txt
```

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

### Custom Annotation Format Example

Source: https://github.com/nextgenusfs/funannotate2/blob/main/funannotate2/data/custom_annotations.template.txt

Example lines demonstrating the format for custom gene/transcript annotations. Each line consists of gene_id, annotation_type, and annotation_value, separated by tabs.

```text
gene123	name	ACT1
gene123	product	Actin
gene123	note	Manually curated annotation
gene456	name	CDC42
gene456	product	Cell division control protein 42
gene789	go_term	GO:0005524
gene789	ec_number	3.6.4.13
```

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

### Using Custom Curated Gene Names and Products

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/annotate.md

Example of how to use a custom annotations file with the --curated-names option.

```bash
funannotate2 annotate -i /path/to/funannotate2_predict_output -o /path/to/output_dir --curated-names /path/to/custom_annotations.txt
```

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

### Clean Genome Assembly

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/API.md

Example of using the Funannotate2 API to clean a genome assembly.

```python
from funannotate2.clean import clean

# Create arguments object
class Args:
    def __init__(self):
        self.input = "genome.fasta"
        self.out = "cleaned_genome.fasta"
        self.minlen = 1000
        self.species = "Aspergillus fumigatus"
        self.strain = "Af293"
        self.header_slice = None
        self.sort = "size"
        self.cpus = 1
        self.tmpdir = None
        self.logfile = None
        self.force = False

args = Args()

# Clean the genome
clean(args)
```

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

### Predict genes using a trained species model

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/species.md

Example of how to use the predict command with a specified trained species model.

```bash
funannotate2 predict -f genome.fasta -o predict_results -p species_name -s "Species name"
```

```bash
funannotate2 predict -f genome.fasta -o predict_results -p aspergillus_fumigatus -s "Aspergillus fumigatus"
```

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

### Fetch genome assembly

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/tutorial.md

Downloads the Aspergillus nidulans FGSCA4 genome assembly and GFF3 file from NCBI.

```bash
wget https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/011/425/GCF_000011425.1_ASM1142v1/GCF_000011425.1_ASM1142v1_genomic.fna.gz
wget https://ftp.ncbi.nlm.nih.gov/genomes/all/GCF/000/011/425/GCF_000011425.1_ASM1142v1/GCF_000011425.1_ASM1142v1_genomic.gff.gz
```

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

### Annotation stats

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/tutorial.md

Displays annotation statistics for the cleaned GFF3 file.

```bash
$ gfftk stats -f GCF_000011425.1_ASM1142v1_genomic.fna.gz -i FGSCA4.gff3
```

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

### Build Documentation

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/README.md

Navigates to the docs directory and builds the HTML documentation.

```bash
cd docs
make html
```

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

### Train Ab Initio Prediction Tools

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/tutorial.md

Trains ab initio prediction tools using funannotate2 train.

```bash
$ funannotate2 train -f GCF_000011425.1_ASM1142v1_genomic.fna.gz \ 
   -s "Aspergillus nidulans" --strain FGSCA4 --cpus 8 -o anid_f2
```

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

### Delete a species

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/usage.md

Example of deleting a species from the Funannotate2 database.

```bash
funannotate2 species -d species_to_delete
```

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

### Clean up NCBI GFF3 format

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/tutorial.md

Sanitizes the downloaded NCBI GFF3 file using gfftk.

```bash
$ gfftk sanitize -f GCF_000011425.1_ASM1142v1_genomic.fna.gz -g GCF_000011425.1_ASM1142v1_genomic.gff.gz -o FGSCA4.gff3
```

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

### Predict Genes

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/API.md

Example of using the Funannotate2 API to predict genes in a genome assembly.

```python
from funannotate2.predict import predict

# Create arguments object
class Args:
    def __init__(self):
        self.input = "cleaned_genome.fasta"
        self.out = "predict_results"
        self.species = "Aspergillus fumigatus"
        self.strain = "Af293"
        self.protein_evidence = ["proteins.fasta"]
        self.transcript_evidence = ["transcripts.fasta"]
        self.augustus_species = "aspergillus_fumigatus"
        self.genemark_mode = "ES"
        self.busco_db = "fungi"
        self.busco_seed_species = None
        self.min_intron_len = 10
        self.max_intron_len = 3000
        self.min_protein_len = 50
        self.cpus = 1
        self.tmpdir = None
        self.logfile = None
        self.force = False

args = Args()

# Predict genes
predict(args)
```

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

### Annotate Genes

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/API.md

Example of using the Funannotate2 API to functionally annotate predicted genes.

```python
from funannotate2.annotate import annotate

# Create arguments object
class Args:
    def __init__(self):
        self.gff3 = "predict_results/funannotate_predict.gff3"
        self.fasta = "cleaned_genome.fasta"
        self.out = "annotate_results"
        self.species = "Aspergillus fumigatus"
        self.strain = "Af293"
        self.pfam = True
        self.dbcan = True
        self.merops = True
        self.swissprot = True
        self.busco = True
        self.busco_db = "fungi"
        self.cpus = 1
        self.tmpdir = None
        self.logfile = None
        self.force = False

args = Args()

# Annotate genes
annotate(args)
```

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

### Predict Genes

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/tutorial.md

Predicts genes using the trained sets with funannotate2 predict.

```bash
$ funannotate2 predict -i anid_f2 --cpus 8 --strain FGSCA4
```

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

### Basic Usage

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/annotate.md

The basic command to run functional annotation.

```bash
funannotate2 annotate -i /path/to/funannotate2_predict_output -o /path/to/output_dir
```

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

### View trained species in YAML format

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/species.md

Lists all trained species in the database and formats the output as YAML.

```bash
funannotate2 species -f yaml
```

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

### Basic Usage

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/train.md

The basic command to initiate the training process for ab initio gene predictors.

```bash
funannotate2 train -f genome.fasta -s "Aspergillus fumigatus" -o train_results
```

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

### View trained species in JSON format

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/species.md

Lists all trained species in the database and formats the output as JSON.

```bash
funannotate2 species -f json
```

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

### Basic Usage

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/clean.md

The basic usage of the `funannotate2 clean` command.

```bash
funannotate2 clean -f genome.fasta -o cleaned_genome.fasta
```

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

### Basic Usage of funannotate2 predict

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/predict.md

Demonstrates the fundamental command structure for running the gene prediction.

```bash
funannotate2 predict -f genome.fasta -o predict_results -p pretrained_species -s "Aspergillus fumigatus"
```

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

### Funannotate2 Command-Line Interface

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/usage.md

The basic structure for using Funannotate2 commands and options.

```bash
funannotate2 <command> <options>
```

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

### List all trained species

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/species.md

Lists all trained species currently in the funannotate2 database.

```bash
funannotate2 species
```

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

### Running tests with verbose output

Source: https://github.com/nextgenusfs/funannotate2/blob/main/tests/README.md

Command to run tests with detailed output.

```bash
pytest -v
```

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

### Running Integration Tests

Source: https://github.com/nextgenusfs/funannotate2/blob/main/tests/integration/README.md

Commands to run all integration tests, a specific test file, or a specific test.

```bash
# Run all integration tests
pytest tests/integration

# Run a specific test file
pytest tests/integration/test_buscolite_cli.py

# Run a specific test
pytest tests/integration/test_buscolite_cli.py::TestBUSCOliteCLI::test_help_command
```

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

### Running a specific test file

Source: https://github.com/nextgenusfs/funannotate2/blob/main/tests/README.md

Command to run tests from a particular file.

```bash
pytest tests/unit/test_utilities.py
```

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

### Run pytest

Source: https://github.com/nextgenusfs/funannotate2/blob/main/README.md

Executes tests using pytest.

```shell
python -m pytest
```

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

### Run tests with coverage reporting

Source: https://github.com/nextgenusfs/funannotate2/blob/main/README.md

Executes tests with coverage reporting to the terminal.

```shell
python -m pytest --cov=funannotate2 --cov-report=term-missing
```

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

### Running all tests

Source: https://github.com/nextgenusfs/funannotate2/blob/main/tests/README.md

Command to execute all tests using pytest.

```bash
pytest
```

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

### Test Memory Monitoring

Source: https://github.com/nextgenusfs/funannotate2/blob/main/MEMORY_MONITORING.md

Command to run the test suite for memory monitoring functionality.

```bash
python test_memory_monitoring.py
```

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

### Generate HTML coverage report

Source: https://github.com/nextgenusfs/funannotate2/blob/main/README.md

Generates a detailed HTML report of code coverage.

```shell
python scripts/run_coverage.py
```

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

### Functionally Annotate Genes

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/tutorial.md

Adds functional annotation to predicted gene models using funannotate2 annotate.

```bash
$ funannotate2 annotate -i anid_f2/ --cpus 8
```

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

### Running a specific test

Source: https://github.com/nextgenusfs/funannotate2/blob/main/tests/README.md

Command to run a single, specific test case.

```bash
pytest tests/unit/test_utilities.py::TestMergeCoordinates::test_overlapping_intervals
```

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

### Running tests with coverage report

Source: https://github.com/nextgenusfs/funannotate2/blob/main/tests/README.md

Command to run tests and generate a code coverage report.

```bash
pytest --cov=funannotate2
```

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

### Using Trained Parameters with Species Name

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/train.md

How to use the trained parameters by referencing the species name, assuming the parameters have been saved in the funannotate2 database.

```bash
funannotate2 predict -f genome.fasta -o predict_results -p aspergillus_fumigatus -s "Aspergillus fumigatus"
```

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

### Using Trained Parameters with params.json

Source: https://github.com/nextgenusfs/funannotate2/blob/main/docs/train.md

How to use the generated params.json file with the predict command to utilize the trained gene prediction models.

```bash
funannotate2 predict -f genome.fasta -o predict_results -p train_results/params.json -s "Aspergillus fumigatus"
```