def test_beta_clusters():
r = list(crystal.model_clusters([cluster], covs, formula, "age",
crystal.zscore_cluster, method=crystal.Beta, transform=crystal.ilogit, n_cpu=1))
assert len(r) == 1
r = r[0]
for v in ('var', 'n_sites', 'sites', 'time', 'chrom', 'start', 'end'):
assert v in r
def test_model_clusters():
r = list(crystal.model_clusters([cluster], covs, formula, "age",
crystal.zscore_cluster, n_cpu=1))
assert len(r) == 1
r = r[0]
for v in ('var', 'n_sites', 'sites', 'time', 'chrom', 'start', 'end'):
assert v in r
def test_model_clusters():
r = list(
crystal.model_clusters([cluster],
covs,
formula,
"age",
crystal.zscore_cluster,
n_cpu=1))
assert len(r) == 1
r = r[0]
for v in ('var', 'n_sites', 'sites', 'time', 'chrom', 'start', 'end'):
assert v in r
def test_beta_clusters():
r = list(
crystal.model_clusters([cluster],
covs,
formula,
"age",
crystal.zscore_cluster,
method=crystal.Beta,
transform=crystal.ilogit,
n_cpu=1))
assert len(r) == 1
r = r[0]
for v in ('var', 'n_sites', 'sites', 'time', 'chrom', 'start', 'end'):
assert v in r
formula = 'methylation ~ age + gender'
coef = 'gender'
covs = pd.read_csv(covariates_file)
def feature_gen(fname):
for i, d in enumerate(ts.reader(fname, header=False)):
if i == 0: continue
chrom, pos = d[0].split(":")
yield crystal.Feature(chrom, int(pos),
crystal.logit(np.array(map(float, d[1:]))))
cluster_iter = mclust(feature_gen(methylation_file), max_dist=100, max_skip=0)
fmt = "{chrom}\t{start}\t{end}\t{p:.4g}\t{coef:.3f}\t{n_sites:d}"
print(ts.fmt2header(fmt))
for i, c in enumerate(
crystal.model_clusters(cluster_iter,
covs,
formula,
coef,
model_fn=crystal.zscore_cluster,
n_cpu=1)):
print(fmt.format(**c))
if c['p'] < 1e-3 and abs(c['coef']) > 0.2 and c['n_sites'] > 3:
crystal.plot.spaghetti_plot(c, covs)
plt.savefig('/tmp/figure-1.eps')
break
covariates_file = "../../../crystal/tests/covs.csv"
methylation_file = "../../../crystal/tests/meth.txt.gz"
formula = "methylation ~ age + gender"
coef = "gender"
covs = pd.read_csv(covariates_file)
def feature_gen(fname):
for i, d in enumerate(ts.reader(fname, header=False)):
if i == 0:
continue
chrom, pos = d[0].split(":")
yield crystal.Feature(chrom, int(pos), crystal.logit(np.array(map(float, d[1:]))))
cluster_iter = mclust(feature_gen(methylation_file), max_dist=100, max_skip=0)
fmt = "{chrom}\t{start}\t{end}\t{p:.4g}\t{coef:.3f}\t{n_sites:d}"
print(ts.fmt2header(fmt))
for i, c in enumerate(
crystal.model_clusters(cluster_iter, covs, formula, coef, model_fn=crystal.zscore_cluster, n_cpu=1)
):
print(fmt.format(**c))
if c["p"] < 1e-3 and abs(c["coef"]) > 0.2 and c["n_sites"] > 3:
crystal.plot.spaghetti_plot(c, covs)
plt.savefig("/tmp/figure-1.eps")
break