def genotype_ibs_segments(genotype,
id1,
id2,
snps,
error_filter='median',
error_filter_length=5,
margin=0.0,
min_ibs_len_snp=400,
debug=False):
'''Return Identical-by-State (IBS >= 1) segments between two genoypes of samples id1 and id2
in the SNP range [snp[0],snp[1]) (if snp is a tuple) or the subset of SNPs, if snps is an array.
See ibs_segments() for a description of optional parameters.'''
num_snps = genotype.num_snps
g = genotype.data
g1 = recode.recode_single_genotype(g[snps, id1, :])
g2 = recode.recode_single_genotype(g[snps, id2, :])
d = (recode.ibs_state(g1, g2) == 0).astype(np.byte)
# Consider informative or the specified SNPs only
filtered_diff = filter_diff(d, error_filter, error_filter_length)
error_snps = snps[np.nonzero(d - filtered_diff)[0]]
# Detect edges as non-zero gradient points; output sufficiently long segments
if np.size(filtered_diff) == 0:
# No data to consider ==> no IBD intervals can be identified
segments = []
else:
# Convert recombination locations to segments of no recombination; filter short segments
bp = genotype.snp['base_pair']
#print segment.segments_with_value(filtered_diff, 0, min_ibs_len_snp)
segments = [
Segment(((x[0], x[1])), [id1, id2],
(bp[x[0]], segment.stop_bp(bp, x[1], num_snps)),
error_snps=segment.in_segment(error_snps, x),
collapse_to_set=False) for x in
segment.segments_with_value(filtered_diff, 0, min_ibs_len_snp)
]
# Cut segment margins
if margin >= constants.SMALL_FLOAT:
segments = [
s for s in (s.middle_part(
genotype.nearest_snp, bp, margin, collapse_to_set=False)
for s in segments) if s
]
# Restrict errors to those inside segments
segment_set = SegmentSet(segments,
np.array(util.flattened_meshgrid(reduce(list.__add__, (s.error_snps.tolist() for s in segments)),
np.array([id1, id2])), dtype=int) \
if segments else gt.empty_errors_array())
if debug:
print 'ibs_segments()', segment_set
print 'errors', segment_set.errors
return segment_set
def genotype_ibs_segments(genotype, id1, id2, snps,
error_filter='median', error_filter_length=5, margin=0.0,
min_ibs_len_snp=400, debug=False):
'''Return Identical-by-State (IBS >= 1) segments between two genoypes of samples id1 and id2
in the SNP range [snp[0],snp[1]) (if snp is a tuple) or the subset of SNPs, if snps is an array.
See ibs_segments() for a description of optional parameters.'''
num_snps = genotype.num_snps
g = genotype.data
g1 = recode.recode_single_genotype(g[snps, id1, :])
g2 = recode.recode_single_genotype(g[snps, id2, :])
d = (recode.ibs_state(g1, g2) == 0).astype(np.byte)
# Consider informative or the specified SNPs only
filtered_diff = filter_diff(d, error_filter, error_filter_length)
error_snps = snps[np.nonzero(d - filtered_diff)[0]]
# Detect edges as non-zero gradient points; output sufficiently long segments
if np.size(filtered_diff) == 0:
# No data to consider ==> no IBD intervals can be identified
segments = []
else:
# Convert recombination locations to segments of no recombination; filter short segments
bp = genotype.snp['base_pair']
#print segment.segments_with_value(filtered_diff, 0, min_ibs_len_snp)
segments = [Segment(((x[0], x[1])), [id1, id2], (bp[x[0]], segment.stop_bp(bp, x[1], num_snps)),
error_snps=segment.in_segment(error_snps, x), collapse_to_set=False)
for x in segment.segments_with_value(filtered_diff, 0, min_ibs_len_snp)]
# Cut segment margins
if margin >= constants.SMALL_FLOAT:
segments = [s for s in (s.middle_part(genotype.nearest_snp, bp, margin, collapse_to_set=False)
for s in segments) if s]
# Restrict errors to those inside segments
segment_set = SegmentSet(segments,
np.array(util.flattened_meshgrid(reduce(list.__add__, (s.error_snps.tolist() for s in segments)),
np.array([id1, id2])), dtype=int) \
if segments else gt.empty_errors_array())
if debug:
print 'ibs_segments()', segment_set
print 'errors', segment_set.errors
return segment_set
def ibs_diff(g, id1, id2):
'''Return the IBS difference between two haplotypes (0 if IBS >= 1, 1 if IBS = 0).'''
g1, g2 = recode.recode_single_genotype(
g[:, id1, :]), recode.recode_single_genotype(g[:, id2, :])
return (recode.ibs_state(g1, g2) == 0).astype(np.byte)
def ibs_state(g, id1, id2):
'''Return the IBS difference between two haplotypes (IBS=0,1 or 2).'''
g1, g2 = recode.recode_single_genotype(
g[:, id1, :]), recode.recode_single_genotype(g[:, id2, :])
return recode.ibs_state(g1, g2)
def ibs_diff(g, id1, id2):
'''Return the IBS difference between two haplotypes (0 if IBS >= 1, 1 if IBS = 0).'''
g1, g2 = recode.recode_single_genotype(g[:, id1, :]), recode.recode_single_genotype(g[:, id2, :])
return (recode.ibs_state(g1, g2) == 0).astype(np.byte)
def ibs_state(g, id1, id2):
'''Return the IBS difference between two haplotypes (IBS=0,1 or 2).'''
g1, g2 = recode.recode_single_genotype(g[:, id1, :]), recode.recode_single_genotype(g[:, id2, :])
return recode.ibs_state(g1, g2)
