Closed jungminchoilab closed 5 years ago
Hello, hope you are having a relaxing holiday.
I am trying to run your software and encountered a following error (embarassingly the same error that I have reported before) even after following your instruction. Would you be able to look into this?
input file
> x = read.table('loci.tsv_rearranged_v2.txt', 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) > x$cluster[x$cluster == 0] = max(x$cluster) + 1 > clone.colors = NULL > pdf('box_v2.pdf', width = 10, height = 10, 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() null device 1 > > 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 = 5, cluster.center = 'mean', ignore.clusters = NULL, clone.colors = NULL, min.cluster.vaf = 0.01, sum.p = 0.05, alpha = 0.05) Sample 1: LT <-- LT Sample 2: LT.PRE <-- LT.PRE Sample 3: ST <-- ST Using monoclonal model Note: all VAFs were divided by 100 to convert from percentage to proportion. Generating non-parametric boostrap samples... LT : Enumerating clonal architectures... Determining if cluster VAF is significantly positive... Exluding clusters whose VAF < min.cluster.vaf=0.01 Non-positive VAF clusters: 3,1 LT : 2 clonal architecture model(s) found LT.PRE : Enumerating clonal architectures... Determining if cluster VAF is significantly positive... Exluding clusters whose VAF < min.cluster.vaf=0.01 Non-positive VAF clusters: 4,3,6 LT.PRE : 1 clonal architecture model(s) found ST : Enumerating clonal architectures... Determining if cluster VAF is significantly positive... Exluding clusters whose VAF < min.cluster.vaf=0.01 Non-positive VAF clusters: 4,1 ST : 2 clonal architecture model(s) found Finding consensus models across samples... Found 4 consensus model(s) Generating consensus clonal evolution trees across samples... Found 4 consensus model(s) Scoring models... Pruning consensus clonal evolution trees.... Seeding aware pruning is: off Number of unique pruned consensus trees: 1 > y = convert.consensus.tree.clone.to.branch(y) > > 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(3,4,2,6,6)) Error in x0[i] <- x1[which(x$branches == parent)] : replacement has length zero
Figured out a way to troubleshoot. It seems like the founding cluster has to be always "1". After I change it to "1", it seems to be working fine.
Thanks!
Hello, hope you are having a relaxing holiday.
I am trying to run your software and encountered a following error (embarassingly the same error that I have reported before) even after following your instruction. Would you be able to look into this?
input file