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https://github.com/danderson123/amira

A tool to detect acquired AMR genes directly from long read sequencing data.
https://github.com/danderson123/amira

amr assembly bacteria bacterial-genome-analysis epidemiology genotyping graph

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A tool to detect acquired AMR genes directly from long read sequencing data.

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README 

        
# Amira



## Introduction



Amira is an AMR gene detection tool designed to work directly from bacterial long read sequences. Amira makes it easy to reliably identify the AMR genes in a bacterial sample, reduces the time taken to get meaningful results and allows more accurate detection of AMR genes than assembly.



## Overview



Amira leverages the full length of long read sequences to differentiate multi-copy genes by their local genomic context. This is done by first identifying the genes on each sequencing read and using the gene calls to construct a *de Bruijn* graph (DBG) in gene space. Following error correction, the reads containing different copies of multi-copy AMR genes can be clustered together based on their path in the graph, then assembled to obtain the nucleotide sequence.



## Prerequisites



Amira requires Python and three additional non-Python tools for optimal functionality:



- **Python >=3.9,<3.13**.

- **Poetry** to manage the Python dependencies.

- **Pandora** to identify the genes on each sequencing read.

- **minimap2** for sequence alignment.

- **racon** for allele polishing.



## Installation



Follow these steps to install Amira and its dependencies.



### From source



#### Step 1: Clone the Amira Repository



Open a terminal and run the following command to clone the repository and navigate into it:

```bash

git clone https://github.com/Danderson123/Amira && cd Amira

```

#### Step 2: Install Poetry

Amira’s dependencies are managed with Poetry. Install Poetry by running:

```bash

pip install poetry

```

#### Step 3: Install Python Dependencies

Once Poetry is installed, use it to set up Amira’s dependencies:



```bash

poetry install

```

####  Step 4: Install Non-Python Dependencies

Amira requires Pandora, minimap2 and racon. Follow the links below for instructions on building binaries for each tool:



- [Pandora Installation Guide](https://github.com/iqbal-lab-org/pandora?tab=readme-ov-file#installation)

- [minimap2 Installation Guide](https://github.com/lh3/minimap2)

- [racon Installation Guide](https://github.com/isovic/racon)



After installation, make a note of the paths to these binaries as they will be required when running Amira.



### From PyPI



Amira can be installed from PyPI by running:

```bash

pip install amira-amr

```

Amira can then be run with:

```bash

amira --help

```

## Running Amira

Amira can be run on the output of Pandora directly, or from JSON files listing the genes and gene positions on each sequencing read. Below are instructions and an example command for running Amira with the JSON files.



### Running from JSON

To run Amira from the JSON files, you can use this command. You will need to replace `` with the absolute path to the racon binary you made earlier and replace `` with the path to the minimap2 binary.

```

python3 amira/__main__.py --pandoraJSON  --gene-positions  --pandoraConsensus  --readfile  --output  --gene-path  --phenotypes  --racon-path  --minimap2-path  --debug --cores  --sample-reads --filter-contaminants

```



####  JSON example



Some example JSON data can be downloaded from [here](https://drive.google.com/drive/folders/1mQ8JmzVhFiNkgRy5_1iFQrqV2TLNnlQ4). Amira can then be run using this command:

```

python3 amira/__main__.py --pandoraJSON test_data/gene_calls_with_gene_filtering.json --gene-positions test_data/gene_positions_with_gene_filtering.json --pandoraConsensus test_data/pandora.consensus.fq.gz --readfile test_data/SRR23044220_1.fastq.gz --output amira_output --gene-path AMR_alleles_unified.fa --phenotypes AMR_calls.json --racon-path  --minimap2-path  --debug --cores  --sample-reads --filter-contaminants

```



### Running with Pandora

[Pandora](https://github.com/iqbal-lab-org/pandora) uses species-specific reference pan-genomes (panRGs) to identify the genes on each sequencing read. For *Escherichia coli*, a pre-built panRG can be downloaded from [here](https://drive.google.com/file/d/15uyl7iQei3Ikd2d6oI_XbARXiKmxl-2d/view). After installing Pandora, you can call the genes on your sequencing reads using this command:

```bash

pandora map -t  --min-gene-coverage-proportion 0.5 --max-covg 10000 -o pandora_map_output  

```

Amira can then be run directly on the output of Pandora using this command:

```bash

python3 amira/__main__.py --pandoraSam pandora_map_output/*.sam --pandoraConsensus pandora_map_output/pandora.consensus.fq.gz --readfile  --output amira_output --gene-path AMR_alleles_unified.fa --minimum-length-proportion 0.5 --maximum-length-proportion 1.5 --cores  --phenotypes AMR_calls.json --filter-contaminants --sample-reads

 ```



### Additional options

For additional options and configurations, run:

```bash

python3 amira/__main__.py --help

```



## Contributing

If you’d like to contribute to Amira, please follow these steps:



1. Fork the repository.

2. Create a new branch for your feature or bugfix (git checkout -b feature-name).

3. Commit your changes (git commit -m "Description of feature").

4. Push to the branch (git push origin feature-name).

5. Submit a pull request.



## License

This project is licensed under the Apache License 2.0 License. See the LICENSE file for details.



## Contact

For questions, feedback, or issues, please open an issue on GitHub or contact [Daniel Anderson]().



## Additional Resources

* [Pandora Documentation](https://github.com/iqbal-lab-org/pandora/wiki/Usage)