import plotly.express as px
import pandas as pd
import matplotlib.pyplot as plt
import numpy as np
import plotly.io as pio

pio.renderers.default = "notebook"

maf_data = 'Variants_for_allele_frequencies.xlsx'
cmr = pd.read_excel(maf_data, sheet_name="cmrdf", header=0, index_col=False)
cmr.head()
gnomad = pd.read_excel(maf_data, sheet_name="gnomadf", header=0, index_col=False)
gnomad.head()

	Population	Variant	MAF	Color
0	gnomAD	GJB2_chr13-20189546-AC-A (rs80338939)	0.007050	1
1	gnomAD	GJB6_chr13-20223467-G-A (rs104894414)	0.000009	1
2	gnomAD	SLC26A4_chr7-107672182-C-T (rs145254330)	0.000319	1
3	gnomAD	MYO15A_chr17-18149488-TCAGA-T (rs780170125)	0.000181	1
4	gnomAD	CDH23 _chr10-71779316-G-A (rs111033270)	0.000160	1

cmr_fig = px.scatter(
    cmr, 
    x="Variant", 
    y="Population", 
    size="MAF", 
    color="MAF",
    hover_name="Population",
    width=800, height=500
)
cmr_fig.write_image("cameroon_HI-variants_maf_plot.svg")
cmr_fig.write_image("cameroon_HI-variants_maf_plot.pdf")

cmr_fig.show()

gnomad_fig = px.scatter(
    gnomad, 
    x="Variant", 
    y="Population", 
    size="MAF", 
    color="MAF",
    hover_name="Population",
    width=800, height=500, 
)

gnomad_fig.write_image("gnomad-variants_maf_plot.svg")
gnomad_fig.write_image("gnomad-variants_maf_plot.pdf")

gnomad_fig.show()