/
vc_linkage.py
executable file
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vc_linkage.py
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import argparse
from math import log, log10, e
import numpy as np
from scipy.stats import chi2
import pydigree
from pydigree.common import log_base_change
from pydigree.io.sgs import read_germline
from pydigree.stats.mixedmodel import MixedModel, RandomEffect
# Parse Arguments
parser = argparse.ArgumentParser()
parser.add_argument('--ped')
parser.add_argument('--map')
parser.add_argument('--phen')
parser.add_argument('--sgs')
parser.add_argument('--outcome', required=True)
parser.add_argument('--fixefs', nargs='*')
parser.add_argument('--every', default=0.5, type=float,
help='Distance between evaluations (in Mb)')
parser.add_argument('--range', default=None)
parser.add_argument('--onlywithin', action='store_true')
parser.add_argument('--sites', nargs='*', type=int, dest='evalsites')
parser.add_argument('--method', default='FS', dest='maxmethod')
parser.add_argument(
'--verbose', action='store_true', help='Show progress of maximizer')
parser.add_argument('--starts', nargs='*', type=float, default=None,
help='Starting values for the optimizer of the IBD model')
parser.add_argument('--interact', action='store_true')
parser.add_argument('--failhard', action='store_true', help=argparse.SUPPRESS)
parser.add_argument('--out')
args = parser.parse_args()
# Read pedigree data
print 'Reading pedigree'
peds = pydigree.io.read_ped(args.ped)
# Read genotype map data
print 'Reading map'
chroms = pydigree.io.plink.read_map(args.map)
for chrom in chroms:
peds.add_chromosome(chrom)
# Read phenotype data
print 'Reading phenotype data'
pydigree.io.read_phenotypes(peds, args.phen)
# Get valid individuals from phenotypes
analysis_individuals = [x for x in peds.individuals
if args.outcome in x.phenotypes]
# Read SGS data
print 'Reading SGS data'
sgs = read_germline(args.sgs)
print 'Updating references'
sgs.update_segment_references(peds)
print 'Fitting polygenic model'
null_model = MixedModel(peds, outcome=args.outcome, fixed_effects=args.fixefs)
null_model.add_genetic_effect()
null_model.fit_model()
null_model.maximize(method=args.maxmethod, verbose=args.verbose)
null_model.summary()
llik_null = null_model.loglikelihood()
print 'Done'
analysis_individuals = null_model.observations()
def vc_linkage(locus):
ibd_model = MixedModel(
peds, outcome=args.outcome, fixed_effects=args.fixefs)
add_relat_mat = null_model.covariance_matrices[0]
additive = RandomEffect(analysis_individuals,
'additive',
incidence_matrix='eye',
covariance_matrix=add_relat_mat)
ibdmat = sgs.ibd_matrix(analysis_individuals,
locus,
location_type='index',
onlywithin=args.onlywithin)
ranef = RandomEffect(analysis_individuals,
'IBD',
incidence_matrix='eye',
covariance_matrix=ibdmat)
ibd_model.add_random_effect(additive)
ibd_model.add_random_effect(ranef)
ibd_model.fit_model()
ibd_model.maximize(
verbose=args.verbose, method=args.maxmethod, starts=args.starts)
return ibd_model
class VCLResult(object):
def __init__(self, alternative, null):
self.llik_alt = alternative.loglikelihood()
self.llik_null = null.loglikelihood()
@property
def chisq(self):
return -2.0 * self.llik_null + 2.0 * self.llik_alt
@property
def pvalue(self):
return chi2.sf(self.chisq, 1)
@property
def lod(self):
return self.chisq / (2.0 * log(10.0))
outputlist = []
print '{:<10} {:<10} {:<10} {:<10} {:<10}'.format('CHROM',
'BP',
'H2',
'LOD',
'PVAL')
print '-' * 64
for chromidx, chromosome in enumerate(peds.chromosomes):
evaluated_sites = set()
if args.range is None:
pstart, pstop = chromosome.physical_map[0], chromosome.physical_map[-1]
else:
pstart, pstop = [int(x) for x in args.range.split('-')]
if pstart < chromosome.physical_map[0]:
raise ValueError('Range start out of range for genotypes')
if pstop > chromosome.physical_map[-1]:
raise ValueError('Range stop out of range for genotypes')
if not args.evalsites:
evaluation_sites = np.arange(pstart, pstop, args.every * 1e6)
else:
evaluation_sites = args.evalsites
for evaluation_site in evaluation_sites:
markidx = chromosome.closest_marker(evaluation_site)
locus = chromidx, markidx
if locus in evaluated_sites:
continue
try:
ibd_model = vc_linkage(locus)
llik_ibd = ibd_model.loglikelihood()
vc = VCLResult(ibd_model, null_model)
h2 = (ibd_model.variance_components[-2] /
sum(ibd_model.variance_components))
output = ['{:<10}'.format(chromosome.label),
'{:<10}'.format(chromosome.physical_map[markidx]),
'{:<10.2f}'.format(h2 * 100),
'{:<10.3f}'.format(vc.lod),
'{:<10.4g}'.format(vc.pvalue)]
outputlist.append(output)
print ' '.join(str(x) for x in output)
except np.linalg.LinAlgError as e:
print 'Error fitting {}:{}: {}'.format(chromosome.label,
chromosome.physical_map[
markidx],
str(e))
if args.failhard:
raise
else:
pass
if args.interact:
import IPython
IPython.embed()
evaluated_sites.add(locus)
if args.out is not None:
print 'Writing output to {}'.format(args.out)
with open(args.out, 'w') as f:
f.write(','.join(['CHROM', 'BP', 'H2', 'LOD', 'PVAL']) + '\n')
for oline in outputlist:
f.write(','.join(oline) + '\n')