#This code calculates NRF1 intensity in cells
#related to Figure 5
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import scipy.stats as stats
import seaborn as sns
mpl.rcParams.update(mpl.rcParamsDefault)
mpl.rcParams['pdf.fonttype'] = 42
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
directory = '/Users/ardamizrak/HMS Dropbox/Arda Mizrak/AggDD/'
image_values = pd.concat([image_values_high,image_values_low])
image_values.head()
pd.set_option('display.max_rows', None)
pd.set_option('display.max_columns', None)
prot_amount = image_values[['FileName_nucleus', 'Group_Index', 'Group_Number', 'Count_nucleus_obj', 'Intensity_TotalIntensity_NRF1', 'Intensity_TotalIntensity_AggDD', 'Intensity_TotalArea_NRF1_nuc']].copy()
prot_amount['NRF1_per_cell'] = prot_amount['Intensity_TotalIntensity_NRF1']/prot_amount['Count_nucleus_obj']
prot_amount['NRF1_ratio'] = prot_amount['NRF1_per_cell']/prot_amount['Intensity_TotalArea_NRF1_nuc']
sns.boxplot(data = prot_amount, x = 'Group_Number', y = 'NRF1_per_cell', hue = 'Group_Index', palette = 'viridis', fliersize = 0)
sns.stripplot(data = prot_amount, x = 'Group_Number', y = 'NRF1_per_cell', hue = 'Group_Index', color = 'k', s = 8)
plt.ylabel('NRF1 intensity per cell')
sns.despine()
plt.show()
sns.boxplot(data = prot_amount, x = 'Group_Number', y = 'NRF1_ratio', hue = 'Group_Index', palette = 'viridis', fliersize = 0)
sns.stripplot(data = prot_amount, x = 'Group_Number', y = 'NRF1_ratio', hue = 'Group_Index', color = 'k', s = 8)
plt.ylabel('NRF1 nuclear:total signal')
sns.despine()
plt.show()