In [2]:
%matplotlib inline
import matplotlib as mpl
mpl.use('agg')
import os
# os.environ["DISPLAY"] = "localhost:11.0"
import numpy as np
import matplotlib.pyplot as plt
import sys,os
path='/'.join(os.getcwd().split('/')[:-4])
sys.path.insert(1,path)
import Utils.Util as utl
import Utils.Plots as pplt
import pandas as pd
pd.options.display.max_rows = 20;
pd.options.display.expand_frame_repr = True
from IPython.display import display
import pylab as plt
import seaborn as sns
import Scripts.KyrgysHAPH.Util as kutl
import Scripts.KyrgysHAPH.Plot as kplt
import Scripts.HLI.Kyrgyz.IBSScan.IBDScan as ibd
import Scripts.HLI.Kyrgyz.PBS as pbs
pd.options.display.max_colwidth = 2000;
import matplotlib as mpl
In [79]:
i=pd.Series({'CHROM':22,'start':26099429,'end':27203877})
f='/home/arya/POP/HA/GT/chr22.vcf.gz.aa.gz'
reload(utl)
ulsrm
# utl.gz.FreqPop(pop='KGZ')
#
# kutl.ID('HLT')
In [89]:
# pd.concat([a,b]).T.dropna().T
Out[89]:
In [57]:
# MINAC = 3
AFCF=0.05
# a= a[((a.sum(1) > MINAC) & (a.sum(1) < a.shape[1] * MINAC))]
print a.shape
a=a[(a[p1].mean(1) / 2 - a[p2].mean(1) / 2).abs() > AFCF]
print a.shape