### System-wide Database Installation

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Copy the downloaded database directory to the Bakta installation directory for a system-wide setup. This makes the database accessible without specifying a path.

```bash
cp -r db/ <bakta-installation-dir>
```

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

### Manual Database Download and Install

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Manually download a database archive using wget and then install it using the bakta_db install command. Useful if the internal download tool is not preferred.

```bash
wget https://zenodo.org/record/14916843/files/db-light.tar.xz
bakta_db install -i db-light.tar.xz
```

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

### Install Pre-downloaded Bakta Database

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/db.md

Command-line utility to install a pre-downloaded Bakta database tarball. Requires specifying the input tarball path and the output directory for extraction.

```bash
bakta_db install --input /path/to/database.tar.xz --output /data/bakta_db
```

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

### Install Bakta via Pip

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Install Bakta using pip for Python environments. Ensure Python 3 is available.

```bash
python3 -m pip install --user bakta
```

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

### Multiple Outputs with Different Configurations

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/plot.md

Example demonstrating how to generate multiple output plots with different configurations and prefixes.

```bash
# Multiple outputs with different configurations
bakta_plot --prefix features genome.json
bakta_plot --type cog --prefix cog genome.json
```

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

### Install BAKTA using Conda

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/README.md

Install BAKTA and its dependencies using Conda. Ensure you have the correct channels configured.

```bash
# Install
conda install -c conda-forge -c bioconda bakta
```

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

### Replicon Metadata Example

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/configuration.md

Example of the TSV/CSV format for specifying per-sequence properties like original ID, new ID, type, topology, and name.

```plaintext
original_seq_id	new_id	type	topology	name
NODE_1	chr1	chromosome	circular	—
NODE_2	p1	plasmid	c	pXYZ1
NODE_3	—	—	—	—
```

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

### bakta_db install

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/db.md

Installs a pre-downloaded Bakta database tarball. This command extracts a downloaded database archive to a specified output directory.

```APIDOC
## Command: `bakta_db install`

### Description
Install pre-downloaded database tarball.

### Arguments
#### Path Parameters
- **--input, -i** (path) - Required - Path to database tarball (`.tar.xz`)
- **--output, -o** (path) - Required - Output directory for extraction
```

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

### Sequence Selection Formats

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/plot.md

Examples demonstrating how to use the --sequences argument to select specific sequences for plotting, supporting 'all', 1-based numbers, FASTA identifiers, or a mix.

```bash
# All sequences (default)
--sequences all
```

```bash
# By 1-based number
--sequences 1,2,3
```

```bash
# By FASTA identifier
--sequences chr1,chr2,plasmid1
```

```bash
# Mix of numbers and names
--sequences 1,chr2,3
```

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

### Setup Runtime Environment

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/configuration.md

Configures the runtime environment using parsed command-line arguments. This function is automatically called after argument parsing and performs essential validation checks for the database, genome file, and other configuration parameters.

```python
def setup(args: argparse.Namespace):
    """Configure runtime environment from parsed arguments."""
    pass
```

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

### Bakta User-Provided HMMs (Default Format)

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Example of providing user-defined HMM profiles in the default HMMER text format.

```bash
# default
HMMER3/f [3.1b2 | February 2015]
NAME  id
ACC   id
DESC  product
LENG  435
TC    600 600
```

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

### Bakta User-Provided HMMs (Short Format)

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Example of providing user-defined HMM profiles in a short format, including gene and product information in the description.

```bash
# short
NAME  id
ACC   id
DESC  gene~~~product~~~dbxrefs
LENG  435
TC    600 600
```

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

### Bakta User-Provided Proteins (Short Fasta Format)

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Example of providing user-defined protein sequences in a short Fasta format, including gene and product information.

```bash
# short:
>id gene~~~product~~~dbxrefs
MAQ...
```

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

### Example manifest.tsv for ENA Submission

Source: https://github.com/oschwengers/bakta/blob/main/README.md

This is an example manifest.tsv file used for ENA genome submission. It specifies study, sample, assembly details, and file locations.

```bash
$ cat manifest.tsv
STUDY    PRJEB44484
SAMPLE    ERS6291240
ASSEMBLYNAME    GCF
ASSEMBLY_TYPE    isolate
COVERAGE    100
PROGRAM    SPAdes
PLATFORM    Illumina
MOLECULETYPE    genomic DNA
FLATFILE    GCF_000008865.2.embl.gz
CHROMOSOME_LIST    chrom-list.tsv.gz
```

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

### Example FASTA Entry with Custom Thresholds

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/expert-systems.md

An example of a FASTA entry using the long format, specifying custom thresholds for identity and coverage, along with gene, product, and database cross-references.

```fasta
>P00123 85~~~75~~~75~~~myfactor~~~my favorite factor~~~MyDB:P00123,GO:0003674
MSTVSTOP...
```

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

### Example Usage: bakta.psc.search

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/ups-ips-psc.md

Shows how to use the psc.search function to perform a Diamond BLASTP search on CDS features. It then iterates through the successful hits to print sequence and product information.

```python
import bakta.psc as psc

hits, no_hits, low_quality = psc.search(cds_features)
for feat in hits:
    print(f"{feat['sequence']}: {feat['psc']['product']}")
```

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

### Bad Commit Message Example

Source: https://github.com/oschwengers/bakta/blob/main/CONTRIBUTION.md

An example of a poorly formatted commit message that lacks a clear subject and detailed explanation.

```bash
some changes fixing this and that...
```

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

### Custom Configuration and High Resolution Plot

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/plot.md

Example of generating a plot with a custom configuration file, high DPI, and specified size.

```bash
# Custom configuration and high resolution
bakta_plot --config colors.yaml --dpi 600 --size 16 genome.json
```

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

### Pull and Run Bakta Docker Image

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Download the official Bakta Docker image and run it to display help information. This is a convenient way to use Bakta without local installation.

```bash
podman pull oschwengers/bakta
```

```bash
podman run oschwengers/bakta --help
```

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

### Good Commit Message Example

Source: https://github.com/oschwengers/bakta/blob/main/CONTRIBUTION.md

An example of a well-structured commit message following best practices, including an imperative subject line, issue reference, and a detailed body explaining the 'what' and 'why'.

```bash
fix broken link in reports #123

As foo changed their internal data structure in the last release bar, we need to update our external links accordingly.
```

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

### Bakta User-Provided Proteins (Long Fasta Format)

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Example of providing user-defined protein sequences in a long Fasta format, including identity and coverage thresholds.

```bash
# long:
>id min_identity~~~min_query_cov~~~min_subject_cov~~~gene~~~product~~~dbxrefs
MAQ...
```

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

### Basic Plot Generation

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/plot.md

Example of a basic plot generation using the default features type.

```bash
# Basic plot (features type)
bakta_plot genome.json
```

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

### Example: Performing UPS Lookup and Printing Results

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/ups-ips-psc.md

Demonstrates how to use the `ups.lookup` function to find UPS matches for a given set of CDS features. It iterates through the found features and prints their sequence along with the associated UniParc identifier.

```python
import bakta.ups as ups

features_with_ups, features_without_ups = ups.lookup(cds_features)
for feat in features_with_ups:
    print(f"{feat['sequence']}: UniParc={feat['ups'].get('uniparc_id')}")
```

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

### check_db_path

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/config.md

Resolves the database path from arguments, environment variables, or a default installation directory. It follows a specific resolution order and raises SystemExit if the path is invalid.

```APIDOC
## Function: `check_db_path(args: Namespace) -> Path`

Resolve database path from argument, environment variable, or default installation directory.

**Parameters:**

| Parameter | Type | Description |
|-----------|------|-------------|
| `args` | `Namespace` | Parsed arguments containing `db` attribute |

**Return:** `pathlib.Path` — Resolved database directory

**Resolution order:**

1. `args.db` (from `--db` argument)
2. `os.environ['BAKTA_DB']` (from `BAKTA_DB` env var)
3. `<bakta_install_dir>/db` (default installation directory)

**Raises:** `SystemExit` if path doesn't exist or schema version mismatches

**Example:**

```python
import bakta.config as cfg
db_path = cfg.check_db_path(args)
# db_path now contains Path to valid database directory
```
```

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

### Example Usage: bakta.ips.lookup

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/ups-ips-psc.md

Demonstrates how to use the ips.lookup function to retrieve IPS annotations for features that have already undergone UPS lookup. It iterates through the results to print gene and product information.

```python
import bakta.ips as ips

features_with_ips, features_without_ips = ips.lookup(features_with_ups)
for feat in features_with_ips:
    print(f"{feat['gene']}: {feat['product']}")
```

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

### Check Database Path

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/config.md

Resolves the database path based on command-line arguments, environment variables, or a default installation directory. Raises SystemExit if the path is invalid or the schema version mismatches.

```python
def check_db_path(args: Namespace) -> Path:
    """Resolve database path."""

```

```python
import bakta.config as cfg
db_path = cfg.check_db_path(args)
# db_path now contains Path to valid database directory

```

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

### bakta.config.setup

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/config.md

Initializes and validates the runtime configuration from parsed arguments. It sets global configuration variables related to the environment, I/O paths, organism information, annotation options, feature workflow, and performs input validation. Raises SystemExit if validation fails.

```APIDOC
## Function: `setup(args: argparse.Namespace)`

### Description
Initialize and validate runtime configuration from parsed arguments.

### Parameters
#### Path Parameters
- `args` (argparse.Namespace) - Required - Parsed command-line arguments from `bakta.utils.parse_arguments()`

### Return
None (modifies global `bakta.config` module variables)

### Behavior
Validates inputs and populates global configuration variables:
1. **Runtime config** — Set `env`, `threads`, `verbose`, `debug` from args
2. **I/O paths** — Validate and resolve `db_path`, `tmp_path`, `genome_path`, `output_path`
3. **Organism info** — Parse and capitalize/lowercase `genus`, `species`, `strain`, `plasmid`
4. **Annotation options** — Set `complete`, `prodigal_tf`, `translation_table`, `gram`, `locus`, `locus_tag`, `compliant`
5. **Feature workflow** — Set all `skip_*` options
6. **Input validation** — Verify file readability, database schema version, external dependencies

### Raises
`SystemExit` with error message if validation fails (invalid paths, schema mismatch, etc.)

### Example
```python
import sys
import argparse
import bakta.config as cfg
import bakta.utils as bu

args = bu.parse_arguments()
cfg.setup(args)
# Now cfg.threads, cfg.db_path, cfg.verbose, etc. are initialized
print(f"Database: {cfg.db_path}")
print(f"Threads: {cfg.threads}")
print(f"Output: {cfg.output_path}")
```
```

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

### EMBL Format Example

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/output-formats.md

This is an example of the EMBL flatfile format, which is an INSDC-compliant alternative to GenBank. It includes sequence metadata and the sequence itself.

```embl
ID   ECO_CHR  standard;  DNA; linear; UNK; ?; ?; ?; UNK; UNK.
AC   UNKNOWN;
SV   UNKNOWN.1
DT   01-JAN-2024 (Rel. 0, Created)
DE   Escherichia coli (strain K-12).
OS   Escherichia coli
OC   Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales;
OC   Enterobacteriaceae; Escherichia.
FT   source          1..4687549
FT                   /organism="Escherichia coli"
FT                   /strain="K-12"
FT   CDS             190..1157
FT                   /locus_tag="ECO_0001"
FT                   /gene="dnaB"
FT                   /product="DNA polymerase III"
FT                   /db_xref="RefSeq:WP_000123456"
SQ   Sequence 4687549 BP; ???????; ? checksum.
     agctttcatc gactagctag ctacgactac gactacgact agctagctag ctactgactg
     ctacgactac gactacgact agctagctag ctacgactac gactacgact agctagctag
```

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

### main()

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/proteins.md

Main entry point for bulk protein annotation. Parses command-line arguments to configure and execute the annotation pipeline.

```APIDOC
## main()

### Description
Main entry point for bulk protein annotation. Parses command-line arguments to configure and execute the annotation pipeline.

### Method
CLI Command

### Endpoint
N/A (CLI function)

### Parameters
#### Command-line Arguments

**Input/Output:**
- **`<input>`** (path) - Required - Input protein sequences in FASTA format
- **`--db, -d`** (path) - Optional - Database directory (Installation default)
- **`--output, -o`** (path) - Optional - Output directory (Current directory)
- **`--prefix, -p`** (str) - Optional - Output file prefix (Input stem)
- **`--force, -f`** (flag) - Optional - Overwrite existing output (False)

**Annotation:**
- **`--proteins`** (path) - Optional - Trusted protein sequences (None)
- **`--hmms`** (path) - Optional - Trusted HMMs in HMMER format (None)

**General:**
- **`--help, -h`** (flag) - Optional - Show help
- **`--verbose, -v`** (flag) - Optional - Verbose output (False)
- **`--debug`** (flag) - Optional - Debug mode (False)
- **`--threads, -t`** (int) - Optional - Worker threads (CPU count)
- **`--tmp-dir`** (path) - Optional - Temporary directory (OS default)
- **`--version, -V`** (flag) - Optional - Version

### Behavior
1. Parse arguments
2. Setup logging
3. Load input sequences
4. Configure database and temporary directory
5. Run annotation pipeline (UPS, IPS, PSC, PSCC, Expert systems, Functional annotation)
6. Perform hypothetical analysis (Pfam, Protein statistics)
7. Write outputs (TSV, FASTA, JSON)
8. Cleanup temporary directory
```

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

### List Available Bakta Database Versions

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/db.md

Command-line utility to list all available Bakta database versions hosted on Zenodo.

```bash
bakta_db list
# Output: v6.0, v5.2, v5.1, ...
```

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

### JSON Structure Example

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/io.md

This is an example of the expected JSON structure for annotation data, including version, genome, stats, sequences, and features.

```json
{
    "version": {
        "bakta": "1.12.0",
        "db": {"version": "6.0", "type": "full"}
    },
    "genome": {
        "genus": "Escherichia",
        "species": "coli",
        "strain": "...",
        "taxonomy": "Bacteria; ...",
        "gc": 0.507,
        "complete": true
    },
    "stats": {
        "size": 4687549,
        "cds": 4290,
        "trna": 86,
        "rrna": 7,
        ...
    },
    "sequences": [
        {
            "id": "chr",
            "type": "chromosome",
            "topology": "circular",
            "length": 4687549,
            "nt": "AGCT...",
            ...
        }
    ],
    "features": [
        {
            "type": "cds",
            "locus": "ECO_0001",
            "product": "DNA polymerase",
            "gene": "dnaB",
            "start": 190,
            "stop": 1157,
            "strand": "+",
            "aa": "MVSTOP...",
            "db_xrefs": ["RefSeq:WP_000123456", "UniRef100_...", ...],
            ...
        }
    ]
}
```

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

### Install DeepSig on Linux

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Install DeepSig for signal predictions on Linux systems within a Conda environment. Note: DeepSig is not available for MacOS.

```bash
conda install -c conda-forge -c bioconda python=3.8 deepsig
```

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

### Example chrom-list.tsv for ENA Submission

Source: https://github.com/oschwengers/bakta/blob/main/README.md

This is an example chrom-list.tsv file used for ENA genome submission. It lists contigs and their types (chromosome or plasmid).

```bash
$ cat chrom-list.tsv
contig_1    contig_1    circular-chromosome
contig_2    contig_2    circular-plasmid
contig_3    contig_3    circular-plasmid
```

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

### I/O Configuration Variables

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/config.md

Manage input and output paths, database information, and file handling.

```python
version: str                  # Bakta version string
db_path: Path                 # Database directory
db_info: dict                 # {'major': int, 'minor': int, 'type': str}
tmp_path: Path                # Temporary directory
genome_path: Path             # Input genome FASTA path
min_sequence_length: int      # Minimum contig/sequence length
prefix: str                   # Output file prefix
output_path: Path             # Output directory
force: bool                   # Force overwrite flag
```

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

### List Available Bakta Database Versions

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Use this command to see the different versions of the Bakta database that are available for download. Databases come in 'full' and 'light' types.

```bash
bakta_db list
...
```

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

### Initialize and Validate Bakta Configuration

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/config.md

Use this function to set up Bakta's runtime configuration from parsed command-line arguments. It validates inputs and populates global configuration variables like database path, threads, and output path.

```python
import sys
import argparse
import bakta.config as cfg
import bakta.utils as bu

args = bu.parse_arguments()
cfg.setup(args)
# Now cfg.threads, cfg.db_path, cfg.verbose, etc. are initialized
print(f"Database: {cfg.db_path}")
print(f"Threads: {cfg.threads}")
print(f"Output: {cfg.output_path}")
```

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

### GFF3 Format Example

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/output-formats.md

This is an example of the GFF3 format, including the header, sequence region, feature lines, and embedded FASTA sequences. It adheres to the GFF3 specification.

```plaintext
##gff-version 3
##sequence-region chr1 1 4687549
chr1	bakta	CDS	190	1157	.	+	0	ID=eco_1;locus_tag=ECO_0001;gene=dnaB;product=DNA polymerase III
chr1	bakta	tRNA	1500	1573	.	+	.	ID=eco_tRNA_1;locus_tag=ECO_tRNA_0001;product=tRNA-Ala
##FASTA
>chr1
AGCTTTCATCGACTAGCTA...
```

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

### Command-line Invocation of Bakta

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/main.md

Demonstrates how to invoke the Bakta CLI from the command line. Ensure you provide the path to the database and specify an output directory.

```bash
# Command-line invocation
bakta --db /path/to/db --output results/ genome.fasta
```

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

### Download BAKTA Database

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/README.md

Download the full BAKTA database to a specified output directory. This is a prerequisite for annotation.

```bash
# Download database
bakta_db download --output /data/bakta_db --type full
```

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

### GFF3 CDS Feature Example

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/output-formats.md

An example of a GFF3 feature line specifically for a CDS (Coding Sequence). It includes essential attributes like ID, Parent, locus_tag, gene symbol, product, Dbxref, and inference information.

```plaintext
chr1	bakta	CDS	190	1157	.	+	0	ID=eco_1;Parent=gene_1;locus_tag=ECO_0001;gene=dnaB;product=DNA polymerase III;Dbxref=RefSeq:WP_000123456,UniRef100_ABC123;inference=ab initio prediction:Prodigal:v2
```

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

### Feature TSV Example

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/output-formats.md

This example demonstrates the structure of the feature annotation TSV file. It includes columns for locus tag, feature type, genomic location, strand, length, gene symbol, product description, and database cross-references.

```tsv
locus	type	location	strand	length	gene	product	db_xrefs
ECO_0001	CDS	190-1157	+	967	dnaB	DNA polymerase III	RefSeq:WP_000123456;UniRef100_ABC123
ECO_0002	CDS	1190-1400	+	210	-	hypothetical protein	UniRef50_XYZ789
ECO_tRNA_0001	tRNA	1500-1573	+	73	-	RNA-Ala	RFAM:RF00005
```

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

### Execution Time Variables

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/config.md

Record the start and end times of the Bakta execution.

```python
run_start: datetime           # Execution start time
run_end: datetime | None      # Execution end time
```

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

### Download Bakta Database using Docker

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Download a Bakta database to a specified host path using Docker. Ensure the host path is mounted correctly into the container.

```bash
docker run -v /path/to/desired-db-path:/db --entrypoint /bin/bash oschwengers/bakta:latest -c "bakta_db download --output /db --type [light|full]"
```

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

### Custom Label and Size Plot

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/plot.md

Example of generating a plot with a custom label and specified size.

```bash
# Custom label and size
bakta_plot --size 16 --label "E. coli|Chromosome" genome.json
```

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

### Bakta Proteins CLI Usage Help

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Displays the help message for the `bakta_proteins` command, outlining all available arguments and options for input, output, and annotation.

```bash
usage: bakta_proteins [--db DB] [--output OUTPUT] [--prefix PREFIX] [--force]
                      [--proteins PROTEINS]
                      [--help] [--verbose] [--debug] [--threads THREADS] [--tmp-dir TMP_DIR] [--version]
                      <input>

Rapid & standardized annotation of bacterial genomes, MAGs & plasmids

positional arguments:
  <input>               Protein sequences in (zipped) fasta format

Input / Output:
  --db DB, -d DB        Database path (default = <bakta_path>/db). Can also be provided as BAKTA_DB environment variable.
  --output OUTPUT, -o OUTPUT
                        Output directory (default = current working directory)
  --prefix PREFIX, -p PREFIX
                        Prefix for output files
  --force, -f           Force overwriting existing output folder

Annotation:
  --proteins PROTEINS   Fasta file of trusted protein sequences for annotation

General:
  --help, -h            Show this help message and exit
  --verbose, -v         Print verbose information
  --debug               Run Bakta in debug mode. Temp data will not be removed.
  --threads THREADS, -t THREADS
                        Number of threads to use (default = number of available CPUs)
  --tmp-dir TMP_DIR     Location for temporary files (default = system dependent auto detection)
  --version, -V         show program's version number and exit
```

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

### Fetch Available Database Versions

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/db.md

Retrieves a list of available database version tags from Zenodo. Use this to determine which versions can be downloaded.

```python
def fetch_db_versions() -> list:
    """Fetch available DB versions from Zenodo."""
```

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

### BLAST+ Version Command

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/features-rna.md

Command to check the installed version of BLAST+. Ensure version 2.17.0 or higher is used for origin detection.

```bash
blastn -version
```

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

### Bakta Output Customization Arguments

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/INDEX.md

Control the naming and location of output files. Use --prefix for a base name and --output for a directory. The --force option allows overwriting existing files.

```bash
# Output customization
--prefix <name>          # Output file prefix
--output <dir>           # Output directory
--force                  # Overwrite existing
```

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

### Bakta Database Cross-Reference Formats

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/types.md

Examples of standardized formats for database cross-references used in Bakta. These follow the 'source:identifier' pattern.

```python
'UniRef100_ABC123'              # UniRef100 cluster ID
```

```python
'RefSeq:WP_000123456'           # RefSeq NRP accession
```

```python
'UniParc:UPI000ABC123'          # UniParc identifier
```

```python
'EC:1.1.1.1'                    # Enzyme commission number
```

```python
'GO:0003674'                    # Gene ontology ID
```

```python
'COG:COG0001'                   # COG identifier
```

```python
'Pfam:PF00001'                  # Pfam domain
```

```python
'VFDB:VF0123'                   # Virulence factor database ID
```

```python
'amrfinder:AMR_GENE_ID'         # AMRFinderPlus reference
```

```python
'UserProtein:custom_id'         # User-provided protein
```

```python
'SO:0001217'                    # Sequence Ontology (coding sequence)
```

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

### Simple Bakta Genome Analysis

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Basic command to run Bakta on a genome file. Requires a database path.

```bash
bakta --db <db-path> genome.fasta
```

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

### Update AMRFinder Database

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Run this command once to set up AMRFinder's internal database if it's crashing. Alternatively, use Bakta's download logic.

```bash
amrfinder_update --force_update --database <bakta-db>/amrfinderplus-db
```

```bash
bakta_db download --output <bakta-db>
```

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

### COG Functional Plot for Specific Sequence

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/plot.md

Example of generating a COG functional plot for a specific sequence (plasmid1) with a custom prefix.

```bash
# COG functional plot of plasmid only
bakta_plot --sequences plasmid1 --type cog --prefix plasmid1_cog genome.json
```

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

### Main Entry Point for Protein Annotation

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/proteins.md

This is the main function for the bulk protein annotation CLI. It parses arguments, sets up logging, loads input sequences, configures the annotation pipeline, performs various annotation steps, and writes the results.

```python
def main():
    """Annotate protein sequences."""

```

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

### Gap Feature Dictionary Structure

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/types.md

Represents gaps in sequence data. Includes sequence, start and stop positions, and an optional estimated length.

```python
{
    'type': 'gap',
    'sequence': str,
    'start': int,
    'stop': int,
    'strand': str,                   # Not meaningful for gaps
    
    'product': 'gap',
    'estimated_length': int | None,  # Estimated gap size if available
    
    'locus': str
}
```

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

### Download ENA Webin-CLI

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Download the Webin-CLI JAR file for submitting genomes to ENA. Ensure you have the correct version.

```bash
# download ENA Webin-CLI
$ wget https://github.com/enasequence/webin-cli/releases/download/8.1.0/webin-cli-8.1.0.jar
```

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

### Basic Protein Annotation with BAKTA

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/proteins.md

Use this command for a straightforward annotation of protein sequences. Ensure your database path is correctly specified.

```bash
# Basic protein annotation
bakta_proteins --db /path/to/db proteins.fasta
```

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

### Download Bakta Database

Source: https://github.com/oschwengers/bakta/blob/main/README.md

This command downloads a specified type of Bakta database to a given output path. Recommended for obtaining the most recent compatible database version.

```bash
bakta_db download --output <output-path> --type [light|full]
```

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

### Bakta CLI Usage

Source: https://github.com/oschwengers/bakta/blob/main/README.md

This snippet displays the full command-line usage for the Bakta tool, including all available arguments and their descriptions. Use this to understand the various parameters for genome annotation.

```bash
usage: bakta [--db DB] [--min-contig-length MIN_CONTIG_LENGTH] [--prefix PREFIX] [--output OUTPUT] [--force]
             [--genus GENUS] [--species SPECIES] [--strain STRAIN] [--plasmid PLASMID]
             [--complete] [--prodigal-tf PRODIGAL_TF] [--translation-table {11,4,25}] [--gram {+,-,?}]
             [--locus LOCUS] [--locus-tag LOCUS_TAG] [--locus-tag-increment {1,5,10}] [--keep-contig-headers] [--compliant]
             [--replicons REPLICONS] [--regions REGIONS] [--proteins PROTEINS] [--hmms HMMS] [--meta]
             [--skip-trna] [--skip-tmrna] [--skip-rrna] [--skip-ncrna] [--skip-ncrna-region]
             [--skip-crispr] [--skip-cds] [--skip-pseudo] [--skip-sorf] [--skip-gap] [--skip-ori] [--skip-filter] [--skip-plot]
             [--help] [--verbose] [--debug] [--threads THREADS] [--tmp-dir TMP_DIR] [--version]
             <genome>

Rapid & standardized annotation of bacterial genomes, MAGs & plasmids

positional arguments:
  <genome>              Genome sequences in (zipped) fasta format

Input / Output:
  --db DB, -d DB        Database path (default = <bakta_path>/db). Can also be provided as BAKTA_DB environment variable.
  --min-contig-length MIN_CONTIG_LENGTH, -m MIN_CONTIG_LENGTH
                        Minimum contig/sequence size (default = 1; 200 in compliant mode)
  --prefix PREFIX, -p PREFIX
                        Prefix for output files
  --output OUTPUT, -o OUTPUT
                        Output directory (default = current working directory)
  --force, -f           Force overwriting existing output folder (except for current working directory)

Organism:
  --genus GENUS         Genus name
  --species SPECIES     Species name
  --strain STRAIN       Strain name
  --plasmid PLASMID     Plasmid name

Annotation:
  --complete            All sequences are complete replicons (chromosome/plasmid[s])
  --prodigal-tf PRODIGAL_TF
                        Path to existing Prodigal training file to use for CDS prediction
  --translation-table {11,4,25}
                        Translation table: 11/4/25 (default = 11)
  --gram {+,-,?}        Gram type for signal peptide predictions: +/-/? (default = ?)
  --locus LOCUS         Locus prefix (default = 'contig')
  --locus-tag LOCUS_TAG
                        Locus tag prefix (default = autogenerated)
  --locus-tag-increment {1,5,10}
                        Locus tag increment: 1/5/10 (default = 1)

  --keep-contig-headers
                        Keep original contig/sequence headers
  --compliant           Force Genbank/ENA/DDJB compliance
  --replicons REPLICONS, -r REPLICONS
                        Replicon information table (tsv/csv)
  --regions REGIONS     Path to pre-annotated regions in GFF3 or Genbank format (regions only, no functional annotations).
  --proteins PROTEINS   Fasta file of trusted protein sequences for CDS annotation
  --hmms HMMS           HMM file of trusted hidden markov models in HMMER format for CDS annotation
  --meta                Run in metagenome mode. This only affects CDS prediction.

Workflow:
  --skip-trna           Skip tRNA detection & annotation
  --skip-tmrna          Skip tmRNA detection & annotation
  --skip-rrna           Skip rRNA detection & annotation
  --skip-ncrna          Skip ncRNA detection & annotation
  --skip-ncrna-region   Skip ncRNA region detection & annotation
  --skip-crispr         Skip CRISPR array detection & annotation
  --skip-cds            Skip CDS detection & annotation
  --skip-pseudo         Skip pseudogene detection & annotation
  --skip-sorf           Skip sORF detection & annotation
  --skip-gap            Skip gap detection & annotation
  --skip-ori            Skip oriC/oriT detection & annotation
  --skip-filter         Skip feature overlap filters
  --skip-plot           Skip generation of circular genome plots

General:
  --help, -h            Show this help message and exit
  --verbose, -v         Print verbose information
  --debug               Run Bakta in debug mode. Temp data will not be removed.
  --threads THREADS, -t THREADS
                        Number of threads to use (default = number of available CPUs)
  --tmp-dir TMP_DIR     Location for temporary files (default = system dependent auto detection)
  --version             show program's version number and exit
```

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

### Get ORFs Function Signature

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/features-rna.md

Defines the function signature for extracting open reading frames (ORFs) from a DNA sequence. Specify the sequence, genetic code table, and minimum ORF length.

```python
def get_orfs(sequence: str, translation_table: int, min_length: int) -> list:
    """Extract all ORFs."""
```

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

### Download Bakta Database

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/db.md

Command-line utility to download and extract Bakta databases from Zenodo. Supports specifying output directory, database type, and download threads. It also handles verification and extraction.

```bash
bakta_db download --output /data/bakta_db --type full
```

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

### Resolve Database Path

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/configuration.md

Determines the database path by checking the `--db` argument, the `BAKTA_DB` environment variable, or the default installation directory. Ensures the database path exists and has a compatible schema version.

```python
def check_db_path(args: Namespace) -> Path:
    """Resolve database path from argument, env var, or installation directory."""
    pass
```

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

### GenBank Flatfile Format (GBFF) Record Structure

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/output-formats.md

This example shows the typical structure of a GenBank flatfile record, including locus information, definition, accession, source, features, and sequence origin. It is INSDC-compliant.

```plaintext
LOCUS       ECO_CHR                4687549 bp    DNA     circular BCT 01-JAN-2024
DEFINITION  Escherichia coli (strain K-12).
ACCESSION   TBD
VERSION     TBD.1
KEYWORDS    .
SOURCE      Escherichia coli
  ORGANISM  Escherichia coli
            Bacteria; Proteobacteria; Gammaproteobacteria; Enterobacterales;
            Enterobacteriaceae; Escherichia.
FEATURES             Location/Qualifiers
     source          1..4687549
                     /organism="Escherichia coli"
                     /strain="K-12"
     gene            190..1157
                     /locus_tag="ECO_0001"
                     /gene="dnaB"
     CDS             190..1157
                     /locus_tag="ECO_0001"
                     /gene="dnaB"
                     /product="DNA polymerase III"
                     /db_xref="RefSeq:WP_000123456"
                     /db_xref="UniRef100_ABC123"
                     /translation="MVSTOP..."
ORIGIN      
        1 agctttcatc gactagctag ctacgactac gactacgact agctagctag ctactgactg
       61 ctacgactac gactacgact agctagctag ctacgactac gactacgact agctagctag
... //
```

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

### fetch_db_versions

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/db.md

Fetches a list of available database versions from Zenodo.

```APIDOC
## Function: `fetch_db_versions()`

### Description
Fetch list of available database versions from Zenodo.

### Return
`list[str]` — List of version tags (e.g., ['v6.0', 'v5.2', ...])
```

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

### Create a single CDS feature dictionary

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/features-cds.md

Use this function to create a single CDS feature dictionary. It requires sequence information, start and stop positions, strand, edge status, and nucleotide and amino acid sequences.

```python
def create_cds(sequence: dict, start: int, stop: int, strand: str, edge: bool, nt: str, aa: str) -> dict:
```

```python
import bakta.features.cds as cds_module

seq = {'id': 'chr1', 'length': 10000}
cds_feat = cds_module.create_cds(seq, 100, 300, '+', False, 'ATGTAG...', 'MVSTOP...')
print(cds_feat['type'])  # 'cds'
print(cds_feat['frame'])  # 1

```

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

### Process JSON Results with bakta_io

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Use the `bakta_io` helper function to create standard output files from a gzipped JSON result file. This is useful for reducing storage requirements for long-term or large-scale projects. The `--output` and `--prefix` arguments control the output path and file prefix, respectively.

```bash
bakta_io --output <output-path> --prefix <prefix> result.json.gz
```

```bash
bakta_io --help
```

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

### Basic Protein Bulk Annotation

Source: https://github.com/oschwengers/bakta/blob/main/README.md

Use this command for direct bulk annotation of protein sequences. Ensure you provide the path to your Bakta database.

```bash
bakta_proteins --db <db-path> input.fasta
```

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

### download

Source: https://github.com/oschwengers/bakta/blob/main/_autodocs/api-reference/db.md

Downloads a database tarball from a given URL with progress tracking and support for resumable downloads.

```APIDOC
## Function: `download(db_url: str, tarball_path: Path)`

### Description
Download database tarball from URL with progress tracking.

### Parameters
#### Path Parameters
- **db_url** (str) - Required - Full URL to database tarball
- **tarball_path** (Path) - Required - Target path for downloaded file

### Behavior

- Streams download with progress bar
- Supports resumable downloads
- Validates with MD5 checksum
```