def phaser_stages13(debug=False, print_times=False):
return new_phaser_chain([
prepare_phaser(),
trivial_phaser(),
family_phaser(),
family_child_comparison_phaser(),
], debug=debug, print_times=print_times)
def setUp(self):
'''Load test data and expected results.'''
unittest.TestCase.setUp(self)
# The way to load a pedigree in conjunction with a genotype set is to recode
# its sample IDs to consecutive for easier access by phasers.
self.problem = io.read_plink(pedigree=itu.HUTT_PED, prefix=itu.GENOTYPE_SAMPLE, haplotype=None)
self.phaser = new_phaser_chain([trivial_phaser()])
def setUp(self):
'''Load test data and expected results.'''
unittest.TestCase.setUp(self)
# Test phaser, doesn't matter which here
self.phaser = new_phaser_chain([trivial_phaser()])
# Generate a non-trivial Problem
self.problem = itu.Templates.problem_family(itu.FAMILY13, haplotype=True)
def nuclear_family_phaser(debug=False, print_times=False):
return new_phaser_chain([
prepare_phaser(),
trivial_phaser(),
family_phaser(),
family_child_comparison_phaser(),
family_sib_comparison_phaser(),
], debug=debug, print_times=print_times)
def __build_phaser(options):
'''Bulid and return the phasing processing chain by options - factory method.'''
if options.stage == 0:
# 07-DEC-12: disabling stage 4 (family_sib_comparison_phaser) since it degrades phasing & imputation
chain = [
prepare_phaser(),
trivial_phaser(),
family_phaser(),
family_child_comparison_phaser(),
phase_distant.family_sib_comparison_phaser(),
phase_distant.distant_phaser()
]
elif options.stage == 1: chain = [prepare_phaser(), trivial_phaser()]
elif options.stage == 2: chain = [family_phaser()]
elif options.stage == 3: chain = [family_child_comparison_phaser()]
elif options.stage == 4: chain = [phase_distant.family_sib_comparison_phaser()]
elif options.stage == 5: chain = [phase_distant.distant_phaser()]
return chain
def setUp(self):
'''Load test data and expected results.'''
unittest.TestCase.setUp(self)
# The way to load a pedigree in conjunction with a genotype set is to recode
# its sample IDs to consecutive for easier access by phasers.
self.problem = io.read_plink(pedigree=itu.HUTT_PED,
prefix=itu.GENOTYPE_SAMPLE,
haplotype=None)
self.phaser = new_phaser_chain([trivial_phaser()])
def setUp(self):
'''Load test data and expected results.'''
unittest.TestCase.setUp(self)
# The way to load a pedigree in conjunction with a genotype set is to recode
# its sample IDs to consecutive for easier access by phasers.
self.problem = io.read_plink(prefix=itu.GENOTYPE_DUO, haplotype=None, pedigree=itu.GENOTYPE_DUO + '.tfam')
self.phaser = trivial_phaser()
# Expected results
self.solution = Problem(self.problem.pedigree, io_genotype.read('plink', 'genotype', prefix=itu.GENOTYPE_DUO_SOLUTION))
def phaser_stages13(debug=False, print_times=False):
return new_phaser_chain([
prepare_phaser(),
trivial_phaser(),
family_phaser(),
family_child_comparison_phaser(),
],
debug=debug,
print_times=print_times)
def nuclear_family_phaser(debug=False, print_times=False):
return new_phaser_chain([
prepare_phaser(),
trivial_phaser(),
family_phaser(),
family_child_comparison_phaser(),
family_sib_comparison_phaser(),
],
debug=debug,
print_times=print_times)
def setUp(self):
'''Load test data and expected results.'''
unittest.TestCase.setUp(self)
# The way to load a pedigree in conjunction with a genotype set is to recode
# its sample IDs to consecutive for easier access by phasers.
self.problem = io.read_plink(prefix=itu.GENOTYPE_TRIO, haplotype=None, pedigree=itu.GENOTYPE_TRIO + '.tfam')
self.phaser = trivial_phaser()
# Expected results
self.solution = Problem(self.problem.pedigree, io_genotype.read('plink', 'genotype', prefix=itu.GENOTYPE_TRIO_SOLUTION))
def setUp(self):
'''Load test data and expected results.'''
unittest.TestCase.setUp(self)
# Load test data ready from previous phasing stagees
self.problem = io.read_npz(itu.FAMILY_TOO_ZEROED_STAGE1)
self.family = self.problem.families()[0]
self.phaser = phase_core.PhaseDecorator(FilterChain([trivial_phaser(),
family_phaser(),
family_child_comparison_phaser()]))
self.comparator = ic.ChildComparator(Struct(problem=self.problem, params=PhaseParam()), self.family)
def __build_phaser(options):
'''Bulid and return the phasing processing chain by options - factory method.'''
if options.stage == 0:
# 07-DEC-12: disabling stage 4 (family_sib_comparison_phaser) since it degrades phasing & imputation
chain = [
prepare_phaser(),
trivial_phaser(),
family_phaser(),
family_child_comparison_phaser(),
phase_distant.family_sib_comparison_phaser(),
phase_distant.distant_phaser()
]
elif options.stage == 1:
chain = [prepare_phaser(), trivial_phaser()]
elif options.stage == 2:
chain = [family_phaser()]
elif options.stage == 3:
chain = [family_child_comparison_phaser()]
elif options.stage == 4:
chain = [phase_distant.family_sib_comparison_phaser()]
elif options.stage == 5:
chain = [phase_distant.distant_phaser()]
return chain
def setUp(self):
'''Load test data and expected results.'''
unittest.TestCase.setUp(self)
# Load test data ready from previous phasing stagees
self.problem = io.read_npz(itu.FAMILY13_STAGE2)
self.family = self.problem.families()[0]
self.phaser = phase_core.PhaseDecorator(
FilterChain([
trivial_phaser(),
family_phaser(),
family_child_comparison_phaser()
]))
self.comparator = ic.ChildComparator(
Struct(problem=self.problem, params=PhaseParam()), self.family)
def prepare_and_trivial_phaser(debug=False, print_times=False):
return new_phaser_chain(
[prepare_phaser(), trivial_phaser()],
debug=debug,
print_times=print_times)
The segments obtained on different platforms (chips) should
be similar (in their base-pair beginning and end positions).
Created on August 2, 2013
@author: Oren Livne <*****@*****.**>
============================================================
'''
import impute as im, os, numpy as np, matplotlib.pyplot as P, sys
from impute.kids.hutt_kids import get_sib_ids, read_chip_problem, chip_data_set
from impute.phasing.phase_trivial import trivial_phaser
####################################################################################
if __name__ == '__main__':
path = os.environ['OBER_OUT'] + '/kids'
chrom = 22
debug = 1
num_processes = 1 # 4
params = im.PhaseParam()
sibs = get_sib_ids(path)
sib = 842 # Has high imputation call rate but high re-phasing error rate
chip = 'cytosnp'
p = im.io.read_npz('%s/%s/chr%d/%s.npz' % (path, chip, chrom, chip_data_set(chip)))
# Run stage 1 so that we can step through the code and find why SNP 1700
# is phased to 2,1 instead of 1,2
phaser = trivial_phaser()
problem = phaser.run(p, im.PhaseParam(selected_samples=np.array([842]), debug=True, print_times=True))
def setUp(self):
'''Load test data and expected results.'''
unittest.TestCase.setUp(self)
# The way to load a pedigree in conjunction with a genotype set is to recode
# its sample IDs to consecutive for easier access by phasers.
self.phaser = new_phaser_chain([trivial_phaser(), family_phaser(), family_child_comparison_phaser()])
def prepare_and_trivial_phaser(debug=False, print_times=False):
return new_phaser_chain([
prepare_phaser(),
trivial_phaser()
], debug=debug, print_times=print_times)
============================================================
'''
import impute as im, os, numpy as np, matplotlib.pyplot as P, sys
from impute.kids.hutt_kids import get_sib_ids, read_chip_problem, chip_data_set
from impute.phasing.phase_trivial import trivial_phaser
####################################################################################
if __name__ == '__main__':
path = os.environ['OBER_OUT'] + '/kids'
chrom = 22
debug = 1
num_processes = 1 # 4
params = im.PhaseParam()
sibs = get_sib_ids(path)
sib = 842 # Has high imputation call rate but high re-phasing error rate
chip = 'cytosnp'
p = im.io.read_npz('%s/%s/chr%d/%s.npz' %
(path, chip, chrom, chip_data_set(chip)))
# Run stage 1 so that we can step through the code and find why SNP 1700
# is phased to 2,1 instead of 1,2
phaser = trivial_phaser()
problem = phaser.run(
p,
im.PhaseParam(selected_samples=np.array([842]),
debug=True,
print_times=True))