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Make mutation and cluster plotting single sample compatible #166

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Make mutation and cluster plotting single sample compatible #166

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b6c336d
create.cluster.heatmap.R - single sample compatibility
graceooh Nov 23, 2024
ef84919
create.ccf.summary.heatmap.R - single sample compatibility
graceooh Nov 23, 2024
9652a4b
create.ccf.summary.heatmap - single sample compatibility
graceooh Nov 23, 2024
50c9f74
create.ccf.summary.heatmap - single sample compatibility
graceooh Nov 23, 2024
2fe34a9
create.ccf.summary.heatmap - single sample compatibility
graceooh Nov 23, 2024
2fa6e38
lintr
graceooh Nov 23, 2024
2023c83
support monoclonal for single ssample
graceooh Nov 23, 2024
e974d66
lintr
graceooh Nov 23, 2024
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46 changes: 43 additions & 3 deletions R/create.ccf.summary.heatmap.R
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Original file line number Diff line number Diff line change
Expand Up @@ -92,8 +92,18 @@ create.ccf.summary.heatmap <- function(
xat = sample.xaxis$at
);

same.as.matrix <- !is.matrix(arr)
if (same.as.matrix) {
arr <- as.data.frame(arr)
colnames(arr) <- as.character(unique(DF$ID))
arr <- as.matrix(arr)
hm.args.x <- as.data.frame(arr)
} else {
hm.args.x <- arr
}

hm.args <- list(
x = arr,
x = hm.args.x,
cluster.dimensions = 'none',
xlab.label = 'Clone',
xlab.cex = ifelse(is.null(clone.colours), subplot.xlab.cex, 0),
Expand All @@ -107,7 +117,8 @@ create.ccf.summary.heatmap <- function(
yaxis.cex = subplot.yaxis.cex,
yaxis.fontface = subplot.yaxis.fontface,
print.colour.key = FALSE,
colour.scheme = hm.col.scheme
colour.scheme = hm.col.scheme,
same.as.matrix = same.as.matrix
);

if (add.median.text) {
Expand All @@ -118,14 +129,32 @@ create.ccf.summary.heatmap <- function(
hm.args$text.col <- ifelse(arr > contrast.thres, 'white', 'black');
}

if (same.as.matrix) {
hm.args$yat <- 1.5
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For parameters added here (line 132 - 148), is everything necessary? Generally, we want to avoid hard coding project/user specific params

hm.args$row.pos <- 1.5
}

if (nrow(hm.args.x) == 1 & ncol(hm.args.x) == 1) {
legend.colour.change <- hm.col.scheme[length(hm.col.scheme)]
hm.args$x <- as.data.frame(hm.col.scheme[length(hm.col.scheme)])
hm.args$input.colours <- TRUE
hm.args$clustering.method <- 'none'
hm.args$yat <- 1
hm.args$col.pos <- 1.5
hm.args$row.pos <- 1
legend.col <- hm.col.scheme[length(hm.col.scheme)]
} else {
legend.col <- hm.col.scheme
}

hm <- do.call(BoutrosLab.plotting.general::create.heatmap, hm.args);

legend.ccf <- BoutrosLab.plotting.general::legend.grob(
list(
legend = list(
title = 'CCF',
labels = c(signif(min(arr), 2), rep('', legend.size), signif(max(arr), 2)),
colours = c('white', 'blue'),
colours = legend.col,
border = 'black',
continuous = TRUE,
cex = legend.label.cex
Expand All @@ -137,6 +166,16 @@ create.ccf.summary.heatmap <- function(
);

if (!is.null(clone.colours)) {
if (length(clone.colours) == 1) {
clone.cov <- BoutrosLab.plotting.general::create.heatmap(
x = as.data.frame(clone.colours),
xlab.label = 'Clone',
input.colours = TRUE,
clustering.method = 'none',
print.colour.key = FALSE,
yaxis.tck = 0
);
} else {
clone.cov <- BoutrosLab.plotting.general::create.heatmap(
x = t(clone.colours[rownames(arr)]),
xlab.label = 'Clone',
Expand All @@ -151,6 +190,7 @@ create.ccf.summary.heatmap <- function(
print.colour.key = FALSE,
yaxis.tck = 0
);
}
plot.list <- list(clone.bar, hm, sample.bar, clone.cov);
layout.skip <- c(FALSE, TRUE, FALSE, FALSE, FALSE, TRUE);
layout.height <- 3;
Expand Down
32 changes: 24 additions & 8 deletions R/create.cluster.heatmap.R
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Original file line number Diff line number Diff line change
Expand Up @@ -44,14 +44,30 @@ create.cluster.heatmap <- function(
arr[arr > ccf.limits[2]] <- ccf.limits[2];
}

hm <- create.ccf.heatmap(
x = arr,
cluster.dimensions = 'none',
xlab.label = '',
xaxis.lab = xaxis.label,
colour.scheme = colour.scheme,
...
);
if (!is.matrix(arr)) {
arr <- as.data.frame(arr)
colnames(arr) <- as.character(unique(DF$ID))

hm <- create.ccf.heatmap(
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This is somewhat redundant I think, especially since users can pass through the same.as.matrix and yat arguments to BPGs create.heatmap.

x = arr,
cluster.dimensions = 'none',
xlab.label = '',
xaxis.lab = xaxis.label,
colour.scheme = colour.scheme,
same.as.matrix = TRUE,
yat = 1.5,
...
);
} else {
hm <- create.ccf.heatmap(
x = arr,
cluster.dimensions = 'none',
xlab.label = '',
xaxis.lab = xaxis.label,
colour.scheme = colour.scheme,
...
);
}

cov <- BoutrosLab.plotting.general::create.heatmap(
x = t(clone.colours[snv.order$clone.id]),
Expand Down
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