Question about convert.consensus.tree.clone.to.branch error

[gorden711411]

Hello

I am trying to use clonevol in my data, I have been succeed in the function infer.clonal.models , then I faced some errors when I used the function convert.consensus.tree.clone.to.branch , the following is the error messages.

Error in $<-.data.frame(*tmp*, "samples.with.nonzero.cell.frac", value = character(0)) : replacement has 0 rows, data has 4

The following is my command (sorry for the bad layout )

library(clonevol) loci11<- read.table("02844190/02844190_c1_2.tsv",header = TRUE) loci13<-loci11[which(loci11$cluster!='NA'),] colnames(loci13)[3]<-"variant_allele_frequency" vaf.col.names<- "P" loci13["P"]<-loci13$variant_allele_frequency

y = infer.clonal.models(variants = loci13, cluster.col.name = 'cluster', vaf.col.names = vaf.col.names,

sample.groups = sample.groups,

                    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 = 0.01,
                    sum.p = 0.05,
                    alpha = 0.05)

y <- convert.consensus.tree.clone.to.branch(y, branch.scale = "sqrt")

plot.clonal.models(y,

box plot parameters

             #  box.plot = TRUE,
            #   fancy.boxplot = FALSE,
             #  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',
               # bell plot parameters
               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,
               # node-based consensus tree parameters
               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,
               # branch-based consensus tree parameters
               merged.tree.clone.as.branch = TRUE,
               mtcab.event.sep.char = ',',
               mtcab.branch.text.size = 1,
               mtcab.branch.width = 0.75,
               mtcab.node.size = 3,
               mtcab.node.label.size = 1,
               mtcab.node.text.size = 1.5,
               # cellular population parameters
               cell.plot = TRUE,
               num.cells = 100,
               cell.border.size = 0.25,
               cell.border.color = 'black',
               clone.grouping = 'horizontal',
               #meta-parameters
               scale.monoclonal.cell.frac = TRUE,
               show.score = FALSE,
               cell.frac.ci = TRUE,
               disable.cell.frac = FALSE,
               # output figure parameters
               out.dir = '02844190_1',
               out.format = 'pdf',
               overwrite.output = TRUE,
               width = 8,
               height = 4,
               # vector of width scales for each panel from left to right
               panel.widths = c(4,1,3,1))

My data: 02844190.zip

Can you help me to find out why it failed? Many thanks.

[hdng]

This is a known bug when only one sample is provided. I am working on a fix. In the meanwhile, you can try to add a fake sample identical to the one you have, eg.

loci13$P2 = loci13$P vaf.col.names = c('P', 'P2')

and rerun. The output consensus tree should be the same, except for node annotation that includes P and P2 instead of only P. Just ignore P2.

[gorden711411]

Thank you for your reply. I hope you can fix the bug smoothly. ^.^

[jamescjc123]

hi， i have the same error when one sample is provided， i want to know if the bug has been fixed？ thank you！

[SoloveyMaria]

Hi, i just tried the ClonEvol tutorial with only P sample (instead of P and R samples) and get the same bug still. Is there any new version available? Thanks!

[gorden711411]

Hi, i just tried the ClonEvol tutorial with only P sample (instead of P and R samples) and get the same bug still. Is there any new version available? Thanks!

vaf.col.names<- c("P","R") You should copy the vaf of P to R