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Figures/Methylation/Methylation_Fig4a.md

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+```python
+# Modules to import - get rid of any not used - add to dockfile in github
+import pandas as pd
+import scipy
+import datashader as ds
+from datashader.mpl_ext import dsshow
+import scipy.stats
+import matplotlib.pyplot as plt
+from matplotlib.colors import LinearSegmentedColormap
+import ssl
+from urllib.request import urlopen
+
+```
+
+
+```python
+# import data - make sure to change to data from GSC website
+
+# use ssl to securely open csv before loading into pandas dataframe
+data_loc = 'https://www.bcgsc.ca/downloads/nanopore_pog/Methylation/POG044_BS_Nanopolish_Meth.bed.gz'
+
+context=ssl.create_default_context()
+context.set_ciphers("DEFAULT")
+result = urlopen(data_loc, context=context)
+
+POG044_BS_Nano_df = pd.read_csv(result, sep="\t",header=None, compression='gzip')
+
+```
+
+
+```python
+# get columns of interest and drop null rows - i.e. BS methylation frequency and nanopore frequency
+POG044_BS_Nano_df_filt = POG044_BS_Nano_df.iloc[:,[2,3]].dropna()
+```
+
+
+```python
+# calculate rho and value using pearson correlation for BS and Nanopolish frequencies
+r_BS_Nano, p_BS_Nano = scipy.stats.pearsonr(POG044_BS_Nano_df_filt[2].values, POG044_BS_Nano_df_filt[3].values)
+
+```
+
+
+```python
+#Visualize Methylation Correlation using datashader - use figure axe 
+def using_datashader(ax, x, y):
+
+    # create dataframe
+    df = pd.DataFrame(dict(x=x, y=y))
+
+    # plot data using viridis cmap and 1 to 1 scale 
+    dsartist = dsshow(
+        df,
+        ds.Point("x", "y"),
+        ds.count(),
+        norm="eq_hist",
+        aspect="auto",
+        cmap=viridis_cmap,
+        width_scale=1,
+        height_scale=1,
+        ax=ax
+    )
+
+#viridis cmap
+viridis_cmap = LinearSegmentedColormap.from_list('white_viridis', [
+    (0, '#440053'),
+    (0.20, '#404388'),
+    (0.40, '#2a788e'),
+    (0.60, '#21a784'),
+    (0.80, '#78d151'),
+    (1, '#fde624'),
+], N=256)
+```
+
+
+```python
+
+
+# Plot 5mC Results 
+fig, ax = plt.subplots()
+using_datashader(ax, POG044_BS_Nano_df_filt[2], POG044_BS_Nano_df_filt[3])
+# set background color and make aspect equal
+ax.set_facecolor('#440053')
+ax.set_aspect('equal', adjustable='box')
+# set lables
+plt.ylabel('WGBS', fontsize = 14, weight="bold")
+plt.xlabel('Nanopolish', fontsize = 14, weight="bold")
+plt.xlim(0,1)
+plt.ylim(0,1)
+plt.text(0.5, 1.1, f'Correlation: {round(r_BS_Nano,2)}', transform=ax.transAxes, ha='center', fontsize = 12, weight="bold")
+plt.text(0.5, 1.05, f'N: {len(POG044_BS_Nano_df_filt)}', transform=ax.transAxes, ha='center', fontsize = 12, weight="bold")
+ax.tick_params(axis='both', labelsize=12)
+plt.tight_layout()
+
+plt.savefig("Methylation_Fig4a.pdf", format="pdf", dpi = 70)
+```
+
+
+
+![png](Methylation_Fig4a_files/Methylation_Fig4a_5_0.png)
+
+