CODEWITHSUNDEEP
pythonarraysnumpy
Alice
Alice

Reputation: 191

Combine two columns under one header in Numpy array

I have two Numpy arrays which I need to combine maintaining only certain columns from A - size (888, 1114253), depending on the rows I have in B - size (555861, 3).

The problem is that the header of A is 55730: each column has two values!

In other words I want to get only the columns of A where the header corresponds to the rows in B, but in A each column is "double"

An example will clarify:

A:

family id mum dad  rs1  rs2  rs3  rs4  rs5  rs6  rs7  rs8  rs9  rs10  rs11  rs12
     1  1   4   6   A T  A A  T T  C C  G G  A T  A G  A A  G A  T A  G G  C C 
     2  2   7   9   T A  G A  C T  C T  G A  T T  A A  A C  G G  T A  C C  C T 
     3  3   2   8   T T  G G  C T  C T  G G  A T  A G  A C  G G  T T  C C  C C 
     4  4   5   1   A A  A A  T T  C C  G A  T T  A A  A A  G A  T A  G C  C T

Since in this file each rsxxx column header has two corresponding columns, I have to find a way to put them together, so I can read the file as an array

B:

1  rs1 2345
1  rs2 2346
2  rs5 2348
4  rs8 2351
4 rs12 2360

The desired output is

Output:

 family id mum dad  rs1 rs2 rs5 rs8 rs12
  1      1   4   6  A T A A G G A A C C
  2      2   7   9  T A G A G A A C C T
  3      3   2   8  T T G G G G A C C C
  4      4   5   1  A A A A G A A A C T

Ideas?

On the console

B:

array([['1', 'rs3094315', '752566'],
       ['1', 'rs12562034', '768448'],
       ['1', 'rs3934834', '1005806'],
       ..., 
       ['23', 'rs2032612', '21866491'],
       ['23', 'rs2032621', '21872738'],
       ['23', 'rs2032617', '21896261']], 
      dtype='<S10')

Upvotes: 1

Views: 1879

Answers (1)

askewchan
askewchan

Reputation: 46530

It looks like each column is separated by two spaces, but that each gene pair is separated by one space. If this is so you can use

delimiter='  '   #two spaces

in np.loadtxt:

import numpy as np
from StringIO import StringIO # for example file

a = StringIO("""family  id  mum  dad  rs1  rs2  rs3  rs4  rs5  rs6  rs7  rs8  rs9  rs10  rs11  rs12
1  1   4   6   A T  A A  T T  C C  G G  A T  A G  A A  G A  T A  G G  C C 
2  2   7   9   T A  G A  C T  C T  G A  T T  A A  A C  G G  T A  C C  C T 
3  3   2   8   T T  G G  C T  C T  G G  A T  A G  A C  G G  T T  C C  C C 
4  4   5   1   A A  A A  T T  C C  G A  T T  A A  A A  G A  T A  G C  C T """)


nrs = 12        # number of `rs` columns, for dtype
dt = 'int,'*4 + 'S10,'*nrs

A = np.genfromtxt(a, delimiter='  ', names=True, dtype=dt)

A:

array([ (1, 1, 4, 6, ' A T', 'A A', 'T T', 'C C', 'G G', 'A T', 'A G', 'A A', 'G A', 'T A', 'G G', 'C C'),
       (2, 2, 7, 9, ' T A', 'G A', 'C T', 'C T', 'G A', 'T T', 'A A', 'A C', 'G G', 'T A', 'C C', 'C T'),
       (3, 3, 2, 8, ' T T', 'G G', 'C T', 'C T', 'G G', 'A T', 'A G', 'A C', 'G G', 'T T', 'C C', 'C C'),
       (4, 4, 5, 1, ' A A', 'A A', 'T T', 'C C', 'G A', 'T T', 'A A', 'A A', 'G A', 'T A', 'G C', 'C T')], 
      dtype=[('family', '<i8'), ('id', '<i8'), ('mum', '<i8'), ('dad', '<i8'), ('rs1', 'S10'), ('rs2', 'S10'), ('rs3', 'S10'), ('rs4', 'S10'), ('rs5', 'S10'), ('rs6', 'S10'), ('rs7', 'S10'), ('rs8', 'S10'), ('rs9', 'S10'), ('rs10', 'S10'), ('rs11', 'S10'), ('rs12', 'S10')])

Then to access only the columns from B, do something like this:

b = StringIO("""1  rs1 2345
1  rs2 2346
2  rs5 2348
4  rs8 2351
4 rs12 2360""")

B = np.genfromtxt(b, usecols=[1], dtype='S10')

Now, use A[B]:

A[B]
array([(' A T', 'A A', 'G G', 'A A', 'C C'),
       (' T A', 'G A', 'G A', 'A C', 'C T'),
       (' T T', 'G G', 'G G', 'A C', 'C C'),
       (' A A', 'A A', 'G A', 'A A', 'C T')], 
      dtype=[('rs1', 'S10'), ('rs2', 'S10'), ('rs5', 'S10'), ('rs8', 'S10'), ('rs12', 'S10')])

Or, if you want the first four columns too:

A[['family', 'id', 'mum', 'dad'] + list(B)]
array([(1, 1, 4, 6, ' A T', 'A A', 'G G', 'A A', 'C C'),
       (2, 2, 7, 9, ' T A', 'G A', 'G A', 'A C', 'C T'),
       (3, 3, 2, 8, ' T T', 'G G', 'G G', 'A C', 'C C'),
       (4, 4, 5, 1, ' A A', 'A A', 'G A', 'A A', 'C T')], 
      dtype=[('family', '<i8'), ('id', '<i8'), ('mum', '<i8'), ('dad', '<i8'), ('rs1', 'S10'), ('rs2', 'S10'), ('rs5', 'S10'), ('rs8', 'S10'), ('rs12', 'S10')])

Upvotes: 2

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