How can i find the different alignments for the algorithm Needleman-Wunsch?












0















I want to find the different alignments for the algorithm Needleman-Wunsch
i blocked in Traceback and compute the all best alignment (different alignments )



that's what I've been able to work until now :



import numpy as np
from string import *

gap_penalty = 0
match_award = 1
mismatch_penalty = 0


-------------------------------------------------------



def W_score (n1,n2):
if(n1 == n2):
return 1
else:
return 0


------------------------------------------------------------



def Max_source(di,ho,ve):

pointer = max(di,ho,ve)

if(di == pointer):
return 'D'
elif(ho == pointer):
return 'H'
else:
return 'V'


--------------------------------------------------------



def needleman_wunsch(seq1,seq2):
n = len(seq1) + 1
p = len(seq2) + 1

# initialisation :
M = np.zeros((n,p),dtype = int)
Dir = np.zeros((n,p),dtype = str)

for i in range(n):
M[i][0] =M[i-1][0] + 0
Dir[i][0] = 'V'

for j in range (p):
M[0][j] = 0
Dir [0][j] = 'H'

Dir [0][0] = 0 #Return the first element of the pointer matrix back to 0.
for i in range(1,n):
for j in range(1,p):
di = M[i-1][j-1] + W_score(seq1[i-1],seq2[j-1])
ve = M[i - 1][j] + 0 # because gap_penalty = 0
ho = M[i][j-1] + 0 # //

M[i][j] = max(di,ho,ve)
Dir[i][j] = Max_source(di,ho,ve)
# print("Global Alignments ' Needlman et Wunsch ' ")
print("Matrix of optimal scores M is :")
print (np.matrix(M))
print("n")
print("Matrix of directions Dir is :")
print (np.matrix(Dir))
print(" Score is :")
print(M[i][j])
seq1= ["A","C","G","G","G","T"]
seq2= ["A","C","G"]
needleman_wunsch(seq1,seq2)









share|improve this question





























    0















    I want to find the different alignments for the algorithm Needleman-Wunsch
    i blocked in Traceback and compute the all best alignment (different alignments )



    that's what I've been able to work until now :



    import numpy as np
    from string import *

    gap_penalty = 0
    match_award = 1
    mismatch_penalty = 0


    -------------------------------------------------------



    def W_score (n1,n2):
    if(n1 == n2):
    return 1
    else:
    return 0


    ------------------------------------------------------------



    def Max_source(di,ho,ve):

    pointer = max(di,ho,ve)

    if(di == pointer):
    return 'D'
    elif(ho == pointer):
    return 'H'
    else:
    return 'V'


    --------------------------------------------------------



    def needleman_wunsch(seq1,seq2):
    n = len(seq1) + 1
    p = len(seq2) + 1

    # initialisation :
    M = np.zeros((n,p),dtype = int)
    Dir = np.zeros((n,p),dtype = str)

    for i in range(n):
    M[i][0] =M[i-1][0] + 0
    Dir[i][0] = 'V'

    for j in range (p):
    M[0][j] = 0
    Dir [0][j] = 'H'

    Dir [0][0] = 0 #Return the first element of the pointer matrix back to 0.
    for i in range(1,n):
    for j in range(1,p):
    di = M[i-1][j-1] + W_score(seq1[i-1],seq2[j-1])
    ve = M[i - 1][j] + 0 # because gap_penalty = 0
    ho = M[i][j-1] + 0 # //

    M[i][j] = max(di,ho,ve)
    Dir[i][j] = Max_source(di,ho,ve)
    # print("Global Alignments ' Needlman et Wunsch ' ")
    print("Matrix of optimal scores M is :")
    print (np.matrix(M))
    print("n")
    print("Matrix of directions Dir is :")
    print (np.matrix(Dir))
    print(" Score is :")
    print(M[i][j])
    seq1= ["A","C","G","G","G","T"]
    seq2= ["A","C","G"]
    needleman_wunsch(seq1,seq2)









    share|improve this question



























      0












      0








      0








      I want to find the different alignments for the algorithm Needleman-Wunsch
      i blocked in Traceback and compute the all best alignment (different alignments )



      that's what I've been able to work until now :



      import numpy as np
      from string import *

      gap_penalty = 0
      match_award = 1
      mismatch_penalty = 0


      -------------------------------------------------------



      def W_score (n1,n2):
      if(n1 == n2):
      return 1
      else:
      return 0


      ------------------------------------------------------------



      def Max_source(di,ho,ve):

      pointer = max(di,ho,ve)

      if(di == pointer):
      return 'D'
      elif(ho == pointer):
      return 'H'
      else:
      return 'V'


      --------------------------------------------------------



      def needleman_wunsch(seq1,seq2):
      n = len(seq1) + 1
      p = len(seq2) + 1

      # initialisation :
      M = np.zeros((n,p),dtype = int)
      Dir = np.zeros((n,p),dtype = str)

      for i in range(n):
      M[i][0] =M[i-1][0] + 0
      Dir[i][0] = 'V'

      for j in range (p):
      M[0][j] = 0
      Dir [0][j] = 'H'

      Dir [0][0] = 0 #Return the first element of the pointer matrix back to 0.
      for i in range(1,n):
      for j in range(1,p):
      di = M[i-1][j-1] + W_score(seq1[i-1],seq2[j-1])
      ve = M[i - 1][j] + 0 # because gap_penalty = 0
      ho = M[i][j-1] + 0 # //

      M[i][j] = max(di,ho,ve)
      Dir[i][j] = Max_source(di,ho,ve)
      # print("Global Alignments ' Needlman et Wunsch ' ")
      print("Matrix of optimal scores M is :")
      print (np.matrix(M))
      print("n")
      print("Matrix of directions Dir is :")
      print (np.matrix(Dir))
      print(" Score is :")
      print(M[i][j])
      seq1= ["A","C","G","G","G","T"]
      seq2= ["A","C","G"]
      needleman_wunsch(seq1,seq2)









      share|improve this question
















      I want to find the different alignments for the algorithm Needleman-Wunsch
      i blocked in Traceback and compute the all best alignment (different alignments )



      that's what I've been able to work until now :



      import numpy as np
      from string import *

      gap_penalty = 0
      match_award = 1
      mismatch_penalty = 0


      -------------------------------------------------------



      def W_score (n1,n2):
      if(n1 == n2):
      return 1
      else:
      return 0


      ------------------------------------------------------------



      def Max_source(di,ho,ve):

      pointer = max(di,ho,ve)

      if(di == pointer):
      return 'D'
      elif(ho == pointer):
      return 'H'
      else:
      return 'V'


      --------------------------------------------------------



      def needleman_wunsch(seq1,seq2):
      n = len(seq1) + 1
      p = len(seq2) + 1

      # initialisation :
      M = np.zeros((n,p),dtype = int)
      Dir = np.zeros((n,p),dtype = str)

      for i in range(n):
      M[i][0] =M[i-1][0] + 0
      Dir[i][0] = 'V'

      for j in range (p):
      M[0][j] = 0
      Dir [0][j] = 'H'

      Dir [0][0] = 0 #Return the first element of the pointer matrix back to 0.
      for i in range(1,n):
      for j in range(1,p):
      di = M[i-1][j-1] + W_score(seq1[i-1],seq2[j-1])
      ve = M[i - 1][j] + 0 # because gap_penalty = 0
      ho = M[i][j-1] + 0 # //

      M[i][j] = max(di,ho,ve)
      Dir[i][j] = Max_source(di,ho,ve)
      # print("Global Alignments ' Needlman et Wunsch ' ")
      print("Matrix of optimal scores M is :")
      print (np.matrix(M))
      print("n")
      print("Matrix of directions Dir is :")
      print (np.matrix(Dir))
      print(" Score is :")
      print(M[i][j])
      seq1= ["A","C","G","G","G","T"]
      seq2= ["A","C","G"]
      needleman_wunsch(seq1,seq2)






      python






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      edited Nov 26 '18 at 0:56







      sir_Ouss

















      asked Nov 26 '18 at 0:11









      sir_Ousssir_Ouss

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