81 lines
2.2 KiB
Plaintext
81 lines
2.2 KiB
Plaintext
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#!/usr/bin/python
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import os, sys
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import getopt
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sys.path.append('../..')
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from fluents import dataset
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import numpy
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max_val = numpy.inf
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no_nan = False
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def print_help():
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print
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print "Usage: go-gene-matrix <go-dist-matrix.ftsv> <gene-go-mapping.txt>"
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print
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print "Description:"
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print " Takes a GO term by GO term distance matrix and a file that"
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print " maps GO terms to genes as input arguments and produces a"
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print " dataset that contains the shortest distances between all"
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print " genes and GO terms."
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print
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print "Options:"
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print " -h, --help Show this help text."
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print " -m, --max-dist Trunkate all distances to this value."
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print
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def get_parameters():
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global max_val
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short_opts = "hm:"
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long_opts = ["help", "max-dist="]
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options, params = getopt.getopt(sys.argv[1:], short_opts, long_opts)
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for opt, val in options:
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if opt in ['-h', '--help']:
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print_help()
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sys.exit(0)
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elif opt in ['-m', '--max-dist']:
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max_val = int(val)
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if len(params) < 2:
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print_help()
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sys.exit(1)
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return params
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if __name__ == '__main__':
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params = get_parameters()
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# Read dataset
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fd = open(params[0])
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ds = dataset.read_ftsv(fd)
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array = ds.asarray()
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fd.close()
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# Read mapping
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sorted_keys = []
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mapping = {}
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fd = open(params[1])
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lines = fd.readlines()
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for line in lines:
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values = line.split()
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if len(values) > 0:
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mapping[values[0]] = values[1:]
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sorted_keys.append(values[0])
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# Create new dataset
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matrix = numpy.zeros((len(sorted_keys), ds.shape[0]))
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dim = ds.get_dim_name(0)
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for i, gene in enumerate(sorted_keys):
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for j, go in enumerate(ds[dim]):
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min = max_val
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for go2 in mapping[gene]:
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if ds[dim].has_key(go2) and array[j, ds[dim][go2]] < min:
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min = array[j, ds[dim][go2]]
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matrix[i, j] = min
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out_ds = dataset.Dataset(matrix,
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(('genes', sorted_keys), ('go-terms', ds[dim])),
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"Gene by GO matrix")
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dataset.write_ftsv(sys.stdout, out_ds)
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