hdng
commented
6 years ago A couple of things went wrong:
- clusters need to be continuous integer starting at 1.
- your data/code do not have several variables (clone.colors, sample.groups)
The following code should work with your current data.
library(clonevol)
# read clustering, prepare data for clonevol
x = read.table('YLR107_clonevol_clean.input', header=T, stringsAsFactors=F, sep='\t')
vaf.col.names = grep('.vaf', colnames(x), value=T)
colnames(x) = gsub('.vaf', '', colnames(x))
vaf.col.names = gsub('.vaf', '', vaf.col.names)
# make sure cluster are continuous integer starting at 1
x$cluster[x$cluster == 0] = max(x$cluster) + 1
# let clonevol decide colors
clone.colors = NULL
# plot cluster of variants to make sure clustering is good
pdf('box.pdf', width = 5, height = 5, useDingbats = FALSE, title='')
pp <- plot.variant.clusters(x,
cluster.col.name = 'cluster',
show.cluster.size = FALSE,
cluster.size.text.color = 'blue',
vaf.col.names = vaf.col.names,
vaf.limits = 70,
sample.title.size = 20,
violin = FALSE,
box = FALSE,
jitter = TRUE,
jitter.shape = 1,
jitter.color = clone.colors,
jitter.size = 1,
jitter.alpha = 1,
jitter.center.method = 'median',
jitter.center.size = 1,
jitter.center.color = 'darkgray',
jitter.center.display.value = 'none',
highlight = 'is.driver',
highlight.shape = 21,
highlight.color = 'blue',
highlight.fill.color = 'green',
highlight.note.col.name = 'gene',
highlight.note.size = 2,
order.by.total.vaf = FALSE)
dev.off()
# infer tree
y = infer.clonal.models(variants = x,
cluster.col.name = 'cluster',
vaf.col.names = vaf.col.names,
sample.groups = NULL,
cancer.initiation.model='monoclonal',
subclonal.test = 'bootstrap',
subclonal.test.model = 'non-parametric',
num.boots = 1000,
founding.cluster = 1,
cluster.center = 'mean',
ignore.clusters = NULL,
clone.colors = NULL,
min.cluster.vaf = 0.01,
sum.p = 0.05,
alpha = 0.05)
# always need to run this to prepare tree for plotting
y = convert.consensus.tree.clone.to.branch(y)
# now plot
plot.clonal.models(y,
box.plot = TRUE,
fancy.boxplot = TRUE,
fancy.variant.boxplot.highlight = 'is.driver',
fancy.variant.boxplot.highlight.shape = 21,
fancy.variant.boxplot.highlight.fill.color = 'red',
fancy.variant.boxplot.highlight.color = 'black',
fancy.variant.boxplot.highlight.note.col.name = 'gene',
fancy.variant.boxplot.highlight.note.color = 'blue',
fancy.variant.boxplot.highlight.note.size = 2,
fancy.variant.boxplot.jitter.alpha = 1,
fancy.variant.boxplot.jitter.center.color = 'grey50',
fancy.variant.boxplot.base_size = 12,
fancy.variant.boxplot.plot.margin = 1,
fancy.variant.boxplot.vaf.suffix = '.VAF',
clone.shape = 'bell',
bell.event = TRUE,
bell.event.label.color = 'blue',
bell.event.label.angle = 60,
clone.time.step.scale = 1,
bell.curve.step = 2,
merged.tree.plot = TRUE,
tree.node.label.split.character = NULL,
tree.node.shape = 'circle',
tree.node.size = 30,
tree.node.text.size = 0.5,
merged.tree.node.size.scale = 1.25,
merged.tree.node.text.size.scale = 2.5,
merged.tree.cell.frac.ci = FALSE,
merged.tree.clone.as.branch = TRUE,
mtcab.event.sep.char = ',',
mtcab.branch.text.size = 1,
mtcab.branch.width = 5,
mtcab.node.size = 3,
mtcab.node.label.size = 1,
mtcab.node.text.size = 1.5,
cell.plot = TRUE, num.cells = 100,
cell.border.size = 0.25,
cell.border.color = 'black',
clone.grouping = 'horizontal',
scale.monoclonal.cell.frac = TRUE,
show.score = FALSE,
cell.frac.ci = TRUE,
disable.cell.frac = FALSE,
out.dir = 'output', out.format = 'pdf',
overwrite.output = TRUE,
width = 11, height = 7,
panel.widths = c(3,4,2,4,4))
The results should look like this.
jungminchoilab
Hi Ha,
Archive.zip Thanks for distributing the software. I appreciate your generosity. I generated the input for the Clonevol using pyclone (attached here) and ran the scripts following your instructions until step 4 as shown below without outputting the errors (RData files is also attached).
Now when I tried to plot the trees, i am getting the errors that other users have been reporting which I could not fix even after following the suggestions from you.
I would appreciate it if you can spend time looking into my data and suggest how to fix it. Please let me know if you need additional information.
Best, Jungmin Choi