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Hi, I am trying to find a consensus tree for a three sample patient data. It works for some patients, and I do get the individual sample clonal architecture models, but 0 consensus trees. This has 10 clusters (as Cyclone-VI gives) and founding cluster is 1.
y = infer.clonal.models(variants = x,
cluster.col.name = "cluster",
ccf.col.names = ccf.col.names,
#vaf.col.names = vaf.col.names,
#sample.groups = sample.groups,
sample.groups = NULL,
cancer.initiation.model='polyclonal',
subclonal.test = 'bootstrap',
subclonal.test.model = 'non-parametric',
num.boots = 1000,
founding.cluster = 1,
cluster.center = 'mean',
ignore.clusters = NULL,
clone.colors = clone.colors,
min.cluster.vaf = NULL,
min probability that CCF(clone) is non-negative
sum.p = 0.05,
alpha level in confidence interval estimate for CCF(clone)
Hi, I am trying to find a consensus tree for a three sample patient data. It works for some patients, and I do get the individual sample clonal architecture models, but 0 consensus trees. This has 10 clusters (as Cyclone-VI gives) and founding cluster is 1.
y = infer.clonal.models(variants = x,
cluster.col.name = "cluster",
ccf.col.names = ccf.col.names,
#vaf.col.names = vaf.col.names,
#sample.groups = sample.groups,
sample.groups = NULL,
cancer.initiation.model='polyclonal',
subclonal.test = 'bootstrap',
subclonal.test.model = 'non-parametric',
num.boots = 1000,
founding.cluster = 1,
cluster.center = 'mean',
ignore.clusters = NULL,
clone.colors = clone.colors,
min.cluster.vaf = NULL,
min probability that CCF(clone) is non-negative
sum.p = 0.05,
alpha level in confidence interval estimate for CCF(clone)
alpha = 0.05)
print("flow done")
Output
y = infer.clonal.models(variants = x,
cluster.col.name = "cluster",
ccf.col.names = ccf.col.names,
#vaf.col.names = vaf.col.names,
#sample.groups = sample.groups,
sample.groups = NULL,
cancer.initiation.model='polyclonal',
subclonal.test = 'bootstrap',
subclonal.test.model = 'non-parametric',
num.boots = 1000,
founding.cluster = 1,
cluster.center = 'mean',
ignore.clusters = NULL,
clone.colors = clone.colors,
min.cluster.vaf = NULL,
min probability that CCF(clone) is non-negative
sum.p = 0.05,
alpha level in confidence interval estimate for CCF(clone)
alpha = 0.05)
print("flow done")
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