def qc_problem(problem, index_file=DEFAULT_ID_INDEX, samples=None, snps=None, debug=0,
input_dir=None, segment_location=None, ibd_sample_index=None, debug_sample= -1):
'''Impute the SNPs that have also been genotyped for all samples, and compare with the
imputation result. Returns the phasing Problem and the imputed results.
problem = npz file location or Problem instance.
segment_location = IBD segment repository (segment file or segment index) location.
ibd_sample_index = optional dictionary of IBD-segment-ID-problem-sample-ID. If None, the mapping between the two IDs is assumed to be the identity.
algorithm options:
'index' - Imputation V2 using IBD cliques at each SNP (default).
'interval_tree' - Imputation V1 using interval tree queries on a SmartSegmentSet.'''
# Read input data
p = problem if isinstance(problem, Problem) else im.io.read_npz(problem)
# Select SNPs
if snps is not None: p = p.sub_problem_of_snps(snps)
t = problem_to_imputation_set(p, index_file=index_file)
print p
print t.genotype
# Load IBD index
ibd = im.index.segment_index.SegmentIndex(segment_location if segment_location else '%s/index_segments' % (os.environ['OBER_OUT'],))
# Run imputation
qc(ibd, t, samples=samples, debug=debug, genotype=p.g, ibd_sample_index=ibd_sample_index, debug_sample=debug_sample)
return p, t
def impute_problem(problem, index_file=DEFAULT_ID_INDEX, samples=None, snps=None, debug=0,
input_dir=None, algorithm='index', segment_location=None, ibd_sample_index=None,
remove_partial_calls=False, debug_sample=-1, genotypes_as_is=False):
'''Impute the SNPs that have also been genotyped for all samples, and compare with the
imputation result. Returns the phasing Problem and the imputed results.
problem = npz file location or Problem instance.
segment_location = IBD segment repository (segment file or segment index) location.
ibd_sample_index = optional dictionary of CGI-ID-problem-sample-ID. If None, the mapping between the two IDs is assumed to be the identity.
algorithm options:
'index' - Imputation V2 using IBD cliques at each SNP (default).
'interval_tree' - Imputation V1 using interval tree queries on a SmartSegmentSet.'''
# Read input data
p = problem if isinstance(problem, Problem) else im.io.read_npz(problem)
# Select SNPs
if snps is not None: p = p.sub_problem_of_snps(snps)
t = problem_to_imputation_set(p, index_file=index_file, genotypes_as_is=genotypes_as_is)
print p
print t.genotype
# Run imputation
segment_location = segment_location if segment_location else ('%s/segments.out' % (input_dir,) if algorithm == 'interval_tree'
else '%s/index_segments' % (os.environ['OBER_OUT'],))
print 'IBD segment index at', segment_location
print 'Imputing, algorithm %s ... ' % (algorithm,)
if algorithm == 'interval_tree':
ibd = im.smart_segment_set.SmartSegmentSet.load(p.pedigree.num_genotyped, segment_location)
print 'IBD segments', ibd.size
im.imputation.iibd.impute(p.haplotype, ibd, t, samples=samples, debug=debug, ibd_sample_index=ibd_sample_index)
elif algorithm == 'index':
ibd = im.index.segment_index.SegmentIndex(segment_location)
im.imputation.impute_ibd_index.impute(ibd, t, samples=samples, debug=debug, genotype=p.g, ibd_sample_index=ibd_sample_index, remove_partial_calls=remove_partial_calls, debug_sample=debug_sample)
else:
raise ValueError('Unsupported imputation algorithm ''%s''' % (algorithm,))
return p, t
def impute_problem(
problem,
index_file=DEFAULT_ID_INDEX,
samples=None,
snps=None,
debug=0,
input_dir=None,
algorithm="index",
segment_location=None,
ibd_sample_index=None,
remove_partial_calls=False,
debug_sample=-1,
genotypes_as_is=False,
):
"""Impute the SNPs that have also been genotyped for all samples, and compare with the
imputation result. Returns the phasing Problem and the imputed results.
problem = npz file location or Problem instance.
segment_location = IBD segment repository (segment file or segment index) location.
ibd_sample_index = optional dictionary of CGI-ID-problem-sample-ID. If None, the mapping between the two IDs is assumed to be the identity.
algorithm options:
'index' - Imputation V2 using IBD cliques at each SNP (default).
'interval_tree' - Imputation V1 using interval tree queries on a SmartSegmentSet."""
# Read input data
p = problem if isinstance(problem, Problem) else im.io.read_npz(problem)
# Select SNPs
if snps is not None:
p = p.sub_problem_of_snps(snps)
t = problem_to_imputation_set(p, index_file=index_file, genotypes_as_is=genotypes_as_is)
print p
print t.genotype
# Run imputation
segment_location = (
segment_location
if segment_location
else (
"%s/segments.out" % (input_dir,)
if algorithm == "interval_tree"
else "%s/index_segments" % (os.environ["OBER_OUT"],)
)
)
print "IBD segment index at", segment_location
print "Imputing, algorithm %s ... " % (algorithm,)
if algorithm == "interval_tree":
ibd = im.smart_segment_set.SmartSegmentSet.load(p.pedigree.num_genotyped, segment_location)
print "IBD segments", ibd.size
im.imputation.iibd.impute(p.haplotype, ibd, t, samples=samples, debug=debug, ibd_sample_index=ibd_sample_index)
elif algorithm == "index":
ibd = im.index.segment_index.SegmentIndex(segment_location)
im.imputation.impute_ibd_index.impute(
ibd,
t,
samples=samples,
debug=debug,
genotype=p.g,
ibd_sample_index=ibd_sample_index,
remove_partial_calls=remove_partial_calls,
debug_sample=debug_sample,
)
else:
raise ValueError("Unsupported imputation algorithm " "%s" "" % (algorithm,))
return p, t
