hdng
commented
5 years ago Looking like the cause is that you only have one cluster (hence one clone). I didn't catch this special case but will note this as a bug.
Anw, when you have one clone, you don't learn much via clonevol analysis, eg. you can predict a tree with one node, 100% CCF in all samples w/o running clonevol. Fishplot will be a straight rectangle with 100% CCF throughout all time points/samples.
Hello, I get the following error when running generateFishplotInputs(). Can you please help me fix this? I have attached the input data.txt file for your reference.
f = generateFishplotInputs(results=y) Error in $<-.data.frame(tmp, "parent", value = numeric(0)) : replacement has 0 rows, data has 1
this is my code:
library(clonevol) library(fishplot) ZHQ.ClonEvol.input.txt x <- read.table("ZHQ.ClonEvol.input.txt",header = T,sep = "\t")
x <- aml1$variants
shorten vaf column names as they will be
vaf.col.names <- grep('.vaf', colnames(x), value=T) sample.names <- gsub('.vaf', '', vaf.col.names)
x[, sample.names] <- x[, vaf.col.names] vaf.col.names <- sample.names
prepare sample grouping
sample.groups <- c('P', 'R');
sample.groups <- vaf.col.names names(sample.groups) <- vaf.col.names
setup the order of clusters to display in various plots (later)
x <- x[order(x$cluster),]
clone.colors <- c('#999793', '#8d4891', '#f8e356', '#fe9536', '#d7352e') y = infer.clonal.models(variants = x, cluster.col.name = 'cluster', vaf.col.names = vaf.col.names, sample.groups = sample.groups, cancer.initiation.model='monoclonal', subclonal.test = 'bootstrap', subclonal.test.model = 'non-parametric', num.boots = 1000, founding.cluster = 1, cluster.center = 'mean', ignore.clusters = NULL, clone.colors = clone.colors, min.cluster.vaf = 0.01,
min probability that CCF(clone) is non-negative
sum.p = 0.05,
alpha level in confidence interval estimate for CCF(clone)
alpha = 0.05)
y <- transfer.events.to.consensus.trees(y, x[x$is.driver,], cluster.col.name = 'cluster', event.col.name = 'gene')
y <- convert.consensus.tree.clone.to.branch(y, branch.scale = 'sqrt')
f = generateFishplotInputs(results=y) fishes = createFishPlotObjects(f)
plot with fishplot
pdf('fish.pdf', width=8, height=5) for (i in 1:length(fishes)){ fish = layoutClones(fishes[[i]]) fish = setCol(fish,f$clonevol.clone.colors) fishPlot(fish,shape="spline", title.btm="Patient", cex.title=0.5, vlines=seq(1, length(vaf.col.names)), vlab=vaf.col.names, pad.left=0.5) } dev <- dev.off()