Python bindings for the [Rust FFI](https://github.com/jguhlin/minimap2-rs/) [minimap2](https://github.com/lh3/minimap2/) library. In development! Feedback appreciated!
# Why?
[PyO3](https://github.com/PyO3/pyo3) makes it very easy to create Python libraries via Rust. Further, we can use [Polars](https://github.com/pola-rs/polars) to export results as a dataframe (which can be used as-is, or converted to Pandas). Python allows for faster experimentation with novel algorithms, integration into machine learning pipelines, and provides an opportunity for those not familiar with Rust nor C/C++ to use minimap2.
# Current State
Very early alpha. Please use, and open an issue for any features you need that are missing, and for any bugs you find.
# How to use
## Requirements
Polars and PyArrow, these should be installed when you install minimappers2
## Creating an Aligner Instance
```python
aligner = map_ont()
aligner.threads(4)
```
If you want an alignment performed, rather than just matches, enable .cigar()
```python
aligner = map_hifi()
aligner.cigar()
```
Please note, at this time the following syntax is **NOT** supported:
```python
aligner = map_ont().threads(4).cigar()
```
## Creating an index
```python
aligner.index("ref.fa")
```
To save a built-index, for future processing use:
```python
aligner.index_and_save("ref.fa", "ref.mmi")
```
Then next time you use the index will be faster if you use the saved index instead.
```python
aligner.load_index("ref.mmi")
```
## Aligning a Single Sequence
```python
query = Sequence(seq_name, seq)
aligner.map1(query)
# Example
seq = "CCAGAACGTACAAGGAAATATCCTCAAATTATCCCAAGAATTGTCCGCAGGAAATGGGGATAATTTCAGAAATGAGAG"
result = aligner.map1(Sequence("MySeq", seq))
```
Where seq_name and seq are both strings. The output is a Polars DataFrame.
## Aligning Multiple Sequences
```python
seqs = [Sequence("name of seq 1", seq1),
Sequence("name of seq 2", seq1)]
result = aligner.map(seqs)
```
# Example Notebook
Please see the [example notebook](https://github.com/jguhlin/minimap2-rs/blob/main/minimappers2/example/Exampe.ipynb) for more examples.
## Mapping a file
Please [open an issue](https://github.com/jguhlin/minimap2-rs/issues/new) if you need to map files from this API.
# Results
All results are returned as [Polars](https://github.com/pola-rs/polars) dataframes. You can convert Polars dataframes to Pandas dataframes with [.to_pandas()](https://pola-rs.github.io/polars/py-polars/html/reference/dataframe/api/polars.DataFrame.to_pandas.html#polars.DataFrame.to_pandas)
* Polars is the fastest dataframe library in the Python Ecosystem.
* Polars provides a nice data bridge between Rust and Python.
For more information, please see the [Polars User Guide](https://pola-rs.github.io/polars-book/user-guide/index.html) or the [Polars Guide for Pandas users](https://pola-rs.github.io/polars-book/user-guide/coming_from_pandas.html).
## Example of Results
Here is an image of the resulting dataframe
**NOTE** Mapq, Cigar, and others will not show up unless .cigar() is enabled on the aligner itself.
# Errors
As this is a very-early stage library, error checking is not yet implemented. When things crash you will likely need to restart your python interpreter (jupyter kernel). Let me know what happened and [open an issue](https://github.com/jguhlin/minimap2-rs/issues/new) and I will get to it.
## Compatability
* Windows: Unlikely
* Linux: Likely
* Mac: Unknown
* x86_64: Likely
* aarch64: Unknown
* neon: No (Open an issue)
* Google Colab: No, not sure why though.
# Performance
Effort has been made to make this as performant as possible, but if you need more performance, please use minimap2 directly and import the results.
# Citation
You should cite the minimap2 papers if you use this in your work.
> Li, H. (2018). Minimap2: pairwise alignment for nucleotide sequences.
> *Bioinformatics*, **34**:3094-3100. [doi:10.1093/bioinformatics/bty191][doi]
and/or:
> Li, H. (2021). New strategies to improve minimap2 alignment accuracy.
> *Bioinformatics*, **37**:4572-4574. [doi:10.1093/bioinformatics/btab705][doi2]
# Changelog
## 0.1.0
* Initial Functions implemented
* Return results as Polars dfs
# Funding
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