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annotate distance_matrix_phylip.py @ 19:115b462224cf draft

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planemo upload for repository https://github.com/phac-nml/mob-suite commit 8898f2229ec13917b7d96e20725f3871d9d93e90-dirty
author dfornika
date Fri, 28 Jun 2019 22:17:09 -0400
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115b462224cf planemo upload for repository https://github.com/phac-nml/mob-suite commit 8898f2229ec13917b7d96e20725f3871d9d93e90-dirty
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1 #!/usr/bin/env python
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3 import argparse
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4 import sys
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5 import csv
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6 import numpy as np
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8 from Bio.Phylo.TreeConstruction import DistanceMatrix, DistanceTreeConstructor
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11 def process_input_matrix(input_matrix):
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12 """ Converts an array-of-arrays containting sample IDs and distances
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13 into a BioPython DistanceMatrix object
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14 """
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15 input_matrix.pop(0)
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16 sample_names = [row[0] for row in input_matrix]
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17 for row in input_matrix:
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18 row.pop(0)
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19 distance_matrix = []
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20 for input_matrix_row in input_matrix:
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21 distance_matrix.append([float(i) for i in input_matrix_row])
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22 """ np.tril() converts a matrix like this: [[0 1 2]
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23 [1 0 1]
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24 [2 1 0]]
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25 ...into this: [[0 0 0]
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26 [1 0 0]
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27 [2 1 0]]
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28 ...but what we need to pass to DistanceMatrix() is this: [[0]
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29 [1 0]
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30 [2 1 0]]
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31 ...so that's what the (somewhat cryptic) code below does.
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32 """
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33 distance_matrix = np.tril(np.array(distance_matrix))
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34 num_rows = distance_matrix.shape[0]
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35 """ masking the distance matrix with tril_indices gives a linearized
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36 distance matrix [0 1 0 2 1 0] that we need to re-construct
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37 into [[0], [1, 0], [2, 1, 0]]
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38 """
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39 lower_triangular_idx_mask = np.tril_indices(num_rows)
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40 linear_distance_matrix = distance_matrix[lower_triangular_idx_mask]
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41 distance_matrix = []
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42 min = 0
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43 max = 1
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44 for i in range(num_rows):
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45 distance_matrix.append(linear_distance_matrix[min:max].tolist())
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46 min = max
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47 max = max + (i + 2)
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49 distance_matrix = DistanceMatrix(names=sample_names, matrix=distance_matrix)
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51 return distance_matrix
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53 def main():
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54 parser = argparse.ArgumentParser()
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55 parser.add_argument("--input", dest="input", help="")
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56 args = parser.parse_args()
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57
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58 reader = csv.reader(open(args.input, "r"), delimiter="\t")
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59 input_matrix = list(reader)
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60 # Don't build a tree with fewer than 3 samples, just produce an empty file
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61 if len(input_matrix) < 4:
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62 print('();')
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63 sys.exit(0)
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64 distance_matrix = process_input_matrix(input_matrix)
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65 distance_matrix.format_phylip(sys.stdout)
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66
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67
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68 if __name__ == '__main__':
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69 main()