Metadata-Version: 2.1
Name: pymsaviz
Version: 0.1.0
Summary: MSA visualization python package for sequence analysis
Home-page: https://moshi4.github.io/pyMSAviz/
License: MIT
Keywords: bioinformatics,matplotlib,visualization,sequence-alignment,sequence-analysis
Author: moshi4
Requires-Python: >=3.7.1,<4.0.0
Classifier: Framework :: Matplotlib
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Topic :: Scientific/Engineering :: Bio-Informatics
Requires-Dist: biopython (>=1.79,<2.0)
Requires-Dist: matplotlib (>=3.5.2,<4.0.0)
Project-URL: Repository, https://github.com/moshi4/pyMSAviz/
Description-Content-Type: text/markdown

# pyMSAviz

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## Table of contents

- [Overview](#overview)
- [Installation](#installation)
- [API Usage](#api-usage)
- [CLI Usage](#cli-usage)

## Overview

pyMSAviz is a MSA(Multiple Sequence Alignment) visualization python package for sequence analysis implemented based on matplotlib.
This package is developed for the purpose of easily and beautifully plotting MSA in Python.
pyMSAviz is inspired by [Jalview](https://www.jalview.org/) and [ggmsa](https://github.com/YuLab-SMU/ggmsa) (R package).

![example01.png](https://raw.githubusercontent.com/moshi4/pyMSAviz/main/docs/images/api_example01.png)  
**Fig.1 pyMSAviz simple visualization result**

![example03.png](https://raw.githubusercontent.com/moshi4/pyMSAviz/main/docs/images/api_example03.png)  
**Fig.2 pyMSAviz customized visualization result**

## Installation

`Python 3.7 or later` is required for installation.

**Install PyPI package:**

    pip install pymsaviz

**Install bioconda package:**

    conda install -c conda-forge -c bioconda pymsaviz

## API Usage

Only simple example usage is described in this section.
For more detail, please see [jupyter notebook](https://moshi4.github.io/pyMSAviz/getting_started/) and [API Docs](https://moshi4.github.io/pyMSAviz/api-docs/msaviz/).

### API Example

#### API Example 1

```python
from pymsaviz import MsaViz, get_msa_testdata

msa_file = get_msa_testdata("HIGD2A.fa")
mv = MsaViz(msa_file, wrap_length=60, show_count=True)
mv.savefig("api_example01.png")
```

![example01.png](https://raw.githubusercontent.com/moshi4/pyMSAviz/main/docs/images/api_example01.png)  

#### API Example 2

```python
from pymsaviz import MsaViz, get_msa_testdata

msa_file = get_msa_testdata("MRGPRG.fa")
mv = MsaViz(msa_file, color_scheme="Taylor", wrap_length=80, show_grid=True, show_consensus=True)
mv.savefig("api_example02.png")
```

![example02.png](https://raw.githubusercontent.com/moshi4/pyMSAviz/main/docs/images/api_example02.png)  

### API Example 3

```python
from pymsaviz import MsaViz, get_msa_testdata

msa_file = get_msa_testdata("MRGPRG.fa")
mv = MsaViz(msa_file, end=180, wrap_length=60, show_consensus=True)

# Get MSA position less than 50% consensus identity
pos_ident_less_than_50 = []
ident_list = mv._get_consensus_identity_list()
for pos, ident in enumerate(ident_list, 1):
    if ident <= 50:
        pos_ident_less_than_50.append(pos)

# Add markers
mv.add_markers([1])
mv.add_markers([10, 20], color="orange", marker="o")
mv.add_markers([30, (40, 50), 55], color="green", marker="+")
mv.add_markers(pos_ident_less_than_50, marker="x", color="blue")
# Add text annotations
mv.add_text_annotation((76, 102), "Gap Region", text_color="red", range_color="red")
mv.add_text_annotation((112, 123), "Gap Region", text_color="green", range_color="green")

mv.savefig("api_example03.png")
```

![example03.png](https://raw.githubusercontent.com/moshi4/pyMSAviz/main/docs/images/api_example03.png)  

## CLI Usage

pyMSAviz provides simple MSA visualization CLI.

### Basic Command

    pymsaviz -i [MSA file] -o [MSA visualization file]

### Options

    -i I, --infile I    Input MSA file
    -o O, --outfile O   Output MSA visualization file (*.png|*.jpg|*.svg|*.pdf)
    --format            MSA file format (Default: 'fasta')
    --color_scheme      Color scheme (Default: 'Zappo')
    --start             Start position of MSA visualization (Default: 1)
    --end               End position of MSA visualization (Default: 'MSA Length')
    --wrap_length       Wrap length (Default: None)
    --wrap_space_size   Space size between wrap MSA plot area (Default: 3.0)
    --show_grid         Show grid (Default: OFF)
    --show_count        Show seq char count without gap on right side (Default: OFF)
    --show_consensus    Show consensus sequence (Default: OFF)
    --consensus_color   Consensus identity bar color (Default: '#1f77b4')
    --consensus_size    Consensus identity bar height size (Default: 2.0)
    --dpi               Figure DPI (Default: 300)
    -v, --version       Print version information
    -h, --help          Show this help message and exit

    Available Color Schemes:
    ['Clustal', 'Zappo', 'Taylor', 'Flower', 'Blossom', 'Sunset', 'Ocean', 'Hydrophobicity', 'HelixPropensity', 
     'StrandPropensity', 'TurnPropensity', 'BuriedIndex', 'Nucleotide', 'Purine/Pyrimidine', 'None']

### CLI Example

Click [here](https://github.com/moshi4/pyMSAviz/raw/main/example/example.zip) to download example MSA files.  

#### CLI Example 1

    pymsaviz -i ./example/HIGD2A.fa -o example01.png

![example01.png](https://raw.githubusercontent.com/moshi4/pyMSAviz/main/docs/images/cli_example01.png)  

#### CLI Example 2

    pymsaviz -i ./example/MRGPRG.fa -o example02.png --wrap_length 80 \
             --color_scheme Taylor --show_consensus --show_count

![example02.png](https://raw.githubusercontent.com/moshi4/pyMSAviz/main/docs/images/cli_example02.png)  

#### CLI Example 3

    pymsaviz -i ./example/MRGPRG.fa -o example03.png --start 100 --end 160 \
             --color_scheme Flower --show_grid --show_consensus --consensus_color tomato 

![example03.png](https://raw.githubusercontent.com/moshi4/pyMSAviz/main/docs/images/cli_example03.png)  

