def fit_null_model(self):
null_model = MixedModel(self.pedigrees,
outcome=self.outcome,
fixed_effects=self.fixed_effects)
null_model.add_genetic_effect()
null_model.fit_model()
null_model.maximize(method=self.maximization, verbose=self.verbose)
return null_model
def fit_null_model(self):
null_model = MixedModel(self.pedigrees,
outcome=self.outcome,
fixed_effects=self.fixed_effects)
null_model.add_genetic_effect()
null_model.fit_model()
null_model.maximize(method=self.maximization, verbose=self.verbose)
return null_model
def fit_alternative_model(self):
ibd_model = MixedModel(self.pedigrees,
outcome=self.outcome,
fixed_effects=self.fixed_effects)
ibd_model.add_genetic_effect()
ranef = RandomEffect(self.analysis_individuals,
'IBD',
incidence_matrix='eye',
covariance_matrix=self.ibd_matrix)
ibd_model.add_random_effect(ranef)
ibd_model.fit_model()
ibd_model.maximize(verbose=self.verbose, method=self.maximization)
return ibd_model
def fit_alternative_model(self):
ibd_model = MixedModel(self.pedigrees,
outcome=self.outcome,
fixed_effects=self.fixed_effects)
ibd_model.add_genetic_effect()
ranef = RandomEffect(self.analysis_individuals,
'IBD',
incidence_matrix='eye',
covariance_matrix=self.ibd_matrix)
ibd_model.add_random_effect(ranef)
ibd_model.fit_model()
ibd_model.maximize(verbose=self.verbose, method=self.maximization)
return ibd_model
# 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',