Exploration of GABA Receptors



In [1]:

    
import NotebookImport
from metaPCNA import *









    




importing IPython notebook from metaPCNA






    




importing IPython notebook from Imports






    




importing IPython notebook from Global_Parameters

Prepare data for CYBERSORT input file format



In [106]:

    
f = pd.read_table('/cellar/users/agross/Downloads_Old/LM22.txt',
                 index_col=0)



In [69]:

    
df = matched_tn
df = df.ix[f.index]
df = df.dropna()
df = 2 ** df
df.columns = ['-'.join(c) for c in df.columns]



In [70]:

    
df.shape









    Out[70]:





(513, 1298)



In [71]:

    
df.to_csv('/cellar/users/agross/Desktop/TCGA_for_CIBERSORT.tab', sep='\t')



In [144]:

    
cs = pd.read_csv('/cellar/users/agross/Data/DiffExp/CIBERSORT/CIBERSORT.Output_matched_tn_subread.csv', 
                 index_col=0)
cs = FH.fix_barcode_columns(cs.T).T



In [145]:

    
cs.shape









    Out[145]:





(1298, 25)



In [146]:

    
cs.head(6).T









    Out[146]:






  
    
      
      TCGA-22-4593
      TCGA-22-4609
      TCGA-22-5471
    
    
      
      01
      11
      01
      11
      01
      11
    
  
  
    
      B cells naive
       3.92e-02
       0.01
       0.00
       0.00
       0.00
       0.01
    
    
      B cells memory
       0.00e+00
       0.00
       0.00
       0.00
       0.00
       0.00
    
    
      Plasma cells
       7.83e-02
       0.00
       0.05
       0.00
       0.01
       0.03
    
    
      T cells CD8
       7.31e-02
       0.04
       0.07
       0.09
       0.27
       0.06
    
    
      T cells CD4 naive
       0.00e+00
       0.00
       0.00
       0.00
       0.00
       0.00
    
    
      T cells CD4 memory resting
       2.96e-01
       0.24
       0.17
       0.27
       0.00
       0.11
    
    
      T cells CD4 memory activated
       0.00e+00
       0.00
       0.06
       0.00
       0.09
       0.00
    
    
      T cells follicular helper
       0.00e+00
       0.00
       0.00
       0.00
       0.05
       0.02
    
    
      T cells regulatory (Tregs)
       0.00e+00
       0.00
       0.00
       0.00
       0.02
       0.01
    
    
      T cells gamma delta
       0.00e+00
       0.00
       0.00
       0.00
       0.00
       0.00
    
    
      NK cells resting
       5.64e-02
       0.01
       0.04
       0.10
       0.00
       0.03
    
    
      NK cells activated
       0.00e+00
       0.01
       0.00
       0.00
       0.11
       0.03
    
    
      Monocytes
       0.00e+00
       0.28
       0.00
       0.08
       0.00
       0.05
    
    
      Macrophages M0
       2.32e-01
       0.12
       0.34
       0.12
       0.15
       0.32
    
    
      Macrophages M1
       2.82e-02
       0.02
       0.07
       0.04
       0.11
       0.01
    
    
      Macrophages M2
       2.99e-02
       0.13
       0.19
       0.10
       0.13
       0.17
    
    
      Dendritic cells resting
       5.00e-04
       0.00
       0.00
       0.00
       0.01
       0.01
    
    
      Dendritic cells activated
       0.00e+00
       0.04
       0.00
       0.06
       0.02
       0.00
    
    
      Mast cells resting
       0.00e+00
       0.03
       0.00
       0.00
       0.00
       0.08
    
    
      Mast cells activated
       1.49e-01
       0.01
       0.00
       0.13
       0.02
       0.00
    
    
      Eosinophils
       0.00e+00
       0.00
       0.00
       0.00
       0.00
       0.02
    
    
      Neutrophils
       1.78e-02
       0.05
       0.00
       0.00
       0.00
       0.03
    
    
      P-value
       7.00e-02
       0.01
       0.00
       0.03
       0.00
       0.02
    
    
      Pearson Correlation
       1.39e-01
       0.32
       0.43
       0.21
       0.50
       0.23
    
    
      RMSE
       1.04e+00
       0.96
       0.91
       1.01
       0.87
       1.01



In [147]:

    
v = cs[[c for c in cs.columns if c.startswith('T cells')]].sum(1)
v = v[:, '01'] - v[:, '11']



In [185]:

    
dd = cs.ix[ti(cs['Pearson Correlation'] > .1)].T
dd = dd.xs('01',1,1) - dd.xs('11',1,1)
dd = dd.ix[:-3]
dd.shape









    Out[185]:





(22, 493)



In [186]:

    
r1 = screen_feature(df_s3.ix['GABRD'][:,'11'].ix[dd.columns], pearson_pandas, 
               cs.T.ix[:-3].xs('11',1,1), align=False)
r2 = screen_feature(df_s3.ix['GABRD'][:,'01'].ix[dd.columns], pearson_pandas, 
               cs.T.ix[:-3].xs('01',1,1), align=False)



In [187]:

    
series_scatter(r1.rho, r2.rho)



In [190]:

    
screen_feature(dx.ix['GABRD'], spearman_pandas, dd, align=False).head()









    Out[190]:






  
    
      
      rho
      p
      q
    
  
  
    
      Plasma cells
      -0.33
       1.42e-07
       3.12e-06
    
    
      Monocytes
       0.26
       3.39e-05
       3.72e-04
    
    
      Macrophages M2
      -0.21
       1.18e-03
       8.63e-03
    
    
      Neutrophils
       0.19
       3.12e-03
       1.72e-02
    
    
      Macrophages M0
       0.16
       1.29e-02
       5.68e-02



In [191]:

    
series_scatter(dx.ix['GABRD'], dd.ix['Plasma cells'])



In [180]:

    
b = (cs['T cells regulatory (Tregs)'] > 0).astype(int).unstack().T.diff().ix['11']



In [192]:

    
violin_plot_series(cs['T cells regulatory (Tregs)'])



In [ ]:

	TCGA-22-4593		TCGA-22-4609		TCGA-22-5471
	01	11	01	11	01	11
B cells naive	3.92e-02	0.01	0.00	0.00	0.00	0.01
B cells memory	0.00e+00	0.00	0.00	0.00	0.00	0.00
Plasma cells	7.83e-02	0.00	0.05	0.00	0.01	0.03
T cells CD8	7.31e-02	0.04	0.07	0.09	0.27	0.06
T cells CD4 naive	0.00e+00	0.00	0.00	0.00	0.00	0.00
T cells CD4 memory resting	2.96e-01	0.24	0.17	0.27	0.00	0.11
T cells CD4 memory activated	0.00e+00	0.00	0.06	0.00	0.09	0.00
T cells follicular helper	0.00e+00	0.00	0.00	0.00	0.05	0.02
T cells regulatory (Tregs)	0.00e+00	0.00	0.00	0.00	0.02	0.01
T cells gamma delta	0.00e+00	0.00	0.00	0.00	0.00	0.00
NK cells resting	5.64e-02	0.01	0.04	0.10	0.00	0.03
NK cells activated	0.00e+00	0.01	0.00	0.00	0.11	0.03
Monocytes	0.00e+00	0.28	0.00	0.08	0.00	0.05
Macrophages M0	2.32e-01	0.12	0.34	0.12	0.15	0.32
Macrophages M1	2.82e-02	0.02	0.07	0.04	0.11	0.01
Macrophages M2	2.99e-02	0.13	0.19	0.10	0.13	0.17
Dendritic cells resting	5.00e-04	0.00	0.00	0.00	0.01	0.01
Dendritic cells activated	0.00e+00	0.04	0.00	0.06	0.02	0.00
Mast cells resting	0.00e+00	0.03	0.00	0.00	0.00	0.08
Mast cells activated	1.49e-01	0.01	0.00	0.13	0.02	0.00
Eosinophils	0.00e+00	0.00	0.00	0.00	0.00	0.02
Neutrophils	1.78e-02	0.05	0.00	0.00	0.00	0.03
P-value	7.00e-02	0.01	0.00	0.03	0.00	0.02
Pearson Correlation	1.39e-01	0.32	0.43	0.21	0.50	0.23
RMSE	1.04e+00	0.96	0.91	1.01	0.87	1.01

	rho	p	q
Plasma cells	-0.33	1.42e-07	3.12e-06
Monocytes	0.26	3.39e-05	3.72e-04
Macrophages M2	-0.21	1.18e-03	8.63e-03
Neutrophils	0.19	3.12e-03	1.72e-02
Macrophages M0	0.16	1.29e-02	5.68e-02