# Gene Loci Comparison
Create fancy (bokeh) gene locus plots from GenBank files!
This repository extends the functionality of the excellent [DnaFeaturesViewer](https://edinburgh-genome-foundry.github.io/DnaFeaturesViewer/)
## Setup
```shell
pip install git+https://github.com/MrTomRod/gene_loci_comparison.git
```
## Examples
### Bokeh
This library can also create interactive html/javascript-based plots. Open these files in your browser:
- [single locus](tests/output/locus/test_single_locus_pgap.html)
- [multiple loci with synchronized panning](tests/output/loci/test_multiple_bokeh.html)
### Single locus, specify colors
```python
from gene_loci_comparison import Locus, Loci
import matplotlib
import matplotlib.pyplot as plt
matplotlib.rcParams['font.family'] = "PT Sans Narrow"
locus = Locus(gbk_file='/path/to/file.gbk', locus_tag='FAM3257_001019')
locus_to_color = dict(
FAM3257_001014='#1271c3',
FAM3257_001015='#3171c3',
FAM3257_001016='#5d71c3',
FAM3257_001017='#9371c3',
FAM3257_001018='#b171c3',
FAM3257_001019='#cb71c3',
FAM3257_001020='#ea71c3',
FAM3257_001021='#fd71c3',
# FAM3257_001021='#fd71c3' # last gene: white (default color)
)
locus.colorize(locus_to_color)
ax, _ = locus.plot(figure_width=12)
plt.show()
```
### Multiple loci
```python
from gene_loci_comparison import Loci
import matplotlib
matplotlib.rcParams['font.family'] = "PT Sans Narrow"
# Each locus is made from a gbk-file, a gene identifier and a title (optional)
loci_of_interest = [
dict(gbk='/path/to/file1.gbk', gene='FAM3257_00934', title='title1'),
dict(gbk='/path/to/file2.gbk', gene='FAM3257_000019', title='title2'),
dict(gbk='/path/to/file3.gbk', gene='FAM3257_001020', title='title3'),
]
# Highlight selected genes
locus_to_color_dict = {locus['gene']: '#1984ff' for locus in loci_of_interest}
# Generate loci object
loci = Loci.generate(
loci_of_interest,
locus_to_color_dict=locus_to_color_dict
)
plot = loci.plot(auto_reverse=False)
plot.show()
```
### Multiple loci, autoreversed
To automatically reverse loci based on the direction of the selected genes. Simply set `auto_reverse` to `True`.
### Multiple loci, with GC content
Change plotting method from `plot_multiple` to `plot_multiple_gc`.
```python
plot = loci.plot_gc(
auto_reverse=True,
window_bp=200
)
```
Raw data
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