In [1]:

    

import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns
%matplotlib inline


    

In [2]:

    

sns.set(style='ticks', context='paper', font_scale=1.5)


    

In [3]:

    

df = pd.read_excel('/Users/luke.thompson/singlecell/clusters/rsonly_stats.xlsx')
df


    

    
Out[3]:






  

    

      

      
sar3
      
sar4
      
pro3
      
pro4
    
  
  

    

      
Trad genomes
      
8
      
26
      
13
      
41
    
    

      
Non-RS SAGs
      
0
      
0
      
10
      
99
    
    

      
RS SAGs
      
21
      
21
      
5
      
5
    
    

      
All OGs
      
6506
      
5272
      
9328
      
10439
    
    

      
Red Sea-assoc. OGs
      
3373
      
878
      
1192
      
96
    
  

In [4]:

    

df2 = pd.DataFrame(df.iloc[-2:].stack())
df2.reset_index(inplace=True)
df2.columns = ['Set of OGs', 'clusters', 'count']
df2


    

    
Out[4]:






  

    

      

      
Set of OGs
      
clusters
      
count
    
  
  

    

      
0
      
All OGs
      
sar3
      
6506
    
    

      
1
      
All OGs
      
sar4
      
5272
    
    

      
2
      
All OGs
      
pro3
      
9328
    
    

      
3
      
All OGs
      
pro4
      
10439
    
    

      
4
      
Red Sea-assoc. OGs
      
sar3
      
3373
    
    

      
5
      
Red Sea-assoc. OGs
      
sar4
      
878
    
    

      
6
      
Red Sea-assoc. OGs
      
pro3
      
1192
    
    

      
7
      
Red Sea-assoc. OGs
      
pro4
      
96
    
  

In [9]:

    

sns.barplot(data=df2, x='clusters', y='count', hue='Set of OGs', 
            palette=[sns.xkcd_rgb['light pink'], sns.xkcd_rgb['red']])
plt.ylabel('Count')
plt.xlabel('')
plt.xticks([-0.5, 0.5, 1.5, 2.5],
           ['SAR11 clusters v1\n(%s Red Sea SAGs,\n%s other genomes)' % (df.sar3['RS SAGs'], df.sar3['Trad genomes']+df.sar3['Non-RS SAGs']), 
            'SAR11 clusters v2\n(%s Red Sea SAGs,\n%s other genomes)' % (df.sar4['RS SAGs'], df.sar4['Trad genomes']+df.sar4['Non-RS SAGs']),  
            'Proch. clusters v1\n(%s Red Sea SAGs,\n%s other genomes)' % (df.pro3['RS SAGs'], df.pro3['Trad genomes']+df.pro3['Non-RS SAGs']),  
            'Proch. clusters v2\n(%s Red Sea SAGs,\n%s other genomes)' % (df.pro4['RS SAGs'], df.pro4['Trad genomes']+df.pro4['Non-RS SAGs'])], 
           rotation=30)
plt.tight_layout()
plt.savefig('/Users/luke.thompson/singlecell/plots/rsonly_counts.pdf')


    

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