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Volcano ylim slider [CW-7354]

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This commit is contained in:
Neil Horner 2026-06-18 08:34:14 +00:00
parent cca505faae
commit 58b8582ea5
2 changed files with 96 additions and 14 deletions
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5
CHANGELOG.md
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@ -5,6 +5,7 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
## [v2.0.1]
This patch release of `wf-transcriptomes` handles an additional quantification failure edge case that was not observed before release, and fixes issues encountered by users during joint discovery when providing many samples.
@ -17,6 +18,10 @@ Users of wf-transcriptomes v2.0.0 who have encountered issues during discovery a
- Volcano plot class counts incorrect when `log2FoldChange` or `padj` columns contained NA values.
- Adjusted p-values below 0.001 in the volcano selection table are now shown in scientific notation instead of being rounded to 0.000.
- IGV track not correctly loading in EPI2ME Desktop when a sample consists of a single input BAM.
- Volcano plots now display the full y-axis value range instead of initially setting the range to the 99.9th percentile.
### Added
- Volcano plots now include a slider to control the y-axis range maximum, which can be useful to exclude low p-value outliers.
## [v2.0.0]

105
bin/workflow_glue/volcano.py
View File

@ -1,6 +1,6 @@
"""Interactive volcano plot visualization for differential expression analysis."""
from bokeh.events import DocumentReady, Tap
from bokeh.events import DocumentReady, Reset, Tap
from bokeh.layouts import column as bokeh_column, row as bokeh_row
from bokeh.models import (
AutocompleteInput,
@ -61,6 +61,19 @@ def _class_attr_list(attr):
return [v[attr] for k, v in SIGNIFICANCE_CLASSES.items()]
def _padded_range(start, end, padding_fraction=0.02, min_padding=0.1):
"""Return a lightly padded numeric range for plot axes."""
span = end - start
padding = max(min_padding, span * padding_fraction)
return start - padding, end + padding
def _padded_log_range(start, end, padding_fraction=0.02):
"""Return a lightly padded positive range for log-scaled axes."""
factor = 1 + padding_fraction
return start / factor, end * factor
def _volcano_source_data(data, fold_threshold=1, p_threshold=0.05):
"""Prepare the minimal browser payload for the volcano/MA plot."""
data = data.copy()
@ -108,6 +121,8 @@ def _volcano_source_data(data, fold_threshold=1, p_threshold=0.05):
data["gene_group"] = data["GENEID"]
data["selected_label"] = ""
data["label_x_offset"] = 7
data["label_align"] = "left"
# Transformations and thresholds
data["neg_log10_padj"] = -np.log10(data["padj"])
@ -143,6 +158,8 @@ def _volcano_source_data(data, fold_threshold=1, p_threshold=0.05):
"neg_log10_padj",
"padj",
"selected_label",
"label_x_offset",
"label_align",
"color",
"volcano_class",
]
@ -284,26 +301,22 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
x_min = float(source_data["log2FoldChange"].min())
x_max = float(source_data["log2FoldChange"].max())
y_max = float(source_data["neg_log10_padj"].max())
# Exclude the top 0.1% from the initial axis scaling to prevent outliers dominating
y_init_max = (
np.nanpercentile(
source_data["neg_log10_padj"]
.replace([np.inf, -np.inf], np.nan), 99.9)
)
mean_min = float(source_data["mean_expression"].min())
mean_max = float(source_data["mean_expression"].max())
if x_min == x_max:
x_min -= 1
x_max += 1
x_range_min, x_range_max = _padded_range(x_min, x_max)
if y_max <= 0:
y_max = 1
y_init_max = 1
_, y_axis_max = _padded_range(0, y_max, min_padding=0.2)
if mean_min == mean_max:
mean_min *= 0.9
mean_max *= 1.1
# Log scale requires strictly positive lower bound; baseMean can be 0
_pos_means = source_data["mean_expression"][source_data["mean_expression"] > 0]
mean_min_log = float(_pos_means.min()) if len(_pos_means) > 0 else 0.01
ma_x_range_min, ma_x_range_max = _padded_log_range(mean_min_log, mean_max)
y_threshold = -np.log10(p_threshold)
responsive_slider_title_stylesheet = """
@media screen and (max-width: 1100px) {
@ -422,8 +435,9 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
height=480,
sizing_mode="stretch_width",
tools="pan,wheel_zoom,box_zoom,reset,save",
x_range=Range1d(x_min, x_max, bounds=(x_min, x_max)),
y_range=Range1d(0, y_init_max, bounds=(0, y_max)),
x_range=Range1d(
x_range_min, x_range_max, bounds=(x_range_min, x_range_max)),
y_range=Range1d(0, y_axis_max, bounds=(0, y_axis_max)),
)
vol_fig.toolbar.logo = None
@ -482,8 +496,9 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
y="neg_log10_padj",
text="selected_label",
source=source,
x_offset=7,
x_offset="label_x_offset",
y_offset=7,
text_align="label_align",
text_font_size="10px",
text_color="#111111",
)
@ -500,8 +515,11 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
sizing_mode="stretch_width",
tools="pan,wheel_zoom,box_zoom,reset,save",
x_axis_type="log",
x_range=Range1d(mean_min_log, mean_max, bounds=(mean_min_log, mean_max)),
y_range=Range1d(x_min, x_max, bounds=(x_min, x_max)),
x_range=Range1d(
ma_x_range_min, ma_x_range_max,
bounds=(ma_x_range_min, ma_x_range_max),
),
y_range=Range1d(x_range_min, x_range_max, bounds=(x_range_min, x_range_max)),
)
ma_fig.toolbar.logo = None
ma_fig.visible = False
@ -703,10 +721,22 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
value=f"{p_threshold:.3f}" if p_threshold >= 0.001 else f"{p_threshold:.2e}",
width=80,
)
y_axis_slider = Slider(
title="y-axis maximum",
value=y_axis_max,
start=0.1,
end=max(5, np.ceil(y_axis_max)),
step=0.1,
show_value=False,
orientation="horizontal",
sizing_mode="stretch_width",
stylesheets=[responsive_slider_title_stylesheet],
)
# Setup callbacks for interactivity
update_callback = CustomJS(
args=dict(
source=source,
vol_fig=vol_fig,
selection_state=selection_state,
highlight_source=highlight_source,
selected_source=selected_source,
@ -741,6 +771,8 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
const marker = data.marker;
const volcanoClass = data.volcano_class;
const selectedLabel = data.selected_label;
const labelXOffset = data.label_x_offset;
const labelAlign = data.label_align;
const counts = {
significant_high_effect: 0,
significant_low_effect: 0,
@ -794,13 +826,23 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
i = 0;
while (i !== selectedLabel.length) {
selectedLabel[i] = "";
labelXOffset[i] = 7;
labelAlign[i] = "left";
i += 1;
}
const xRangeStart = vol_fig.x_range.start;
const xRangeEnd = vol_fig.x_range.end;
const xSpan = xRangeEnd - xRangeStart;
const labelFlipThreshold = xRangeEnd - (xSpan * 0.12);
selected.forEach(function(index) {
if (view_toggle.active) {
selectedLabel[index] = identifier_col === "TXNAME"
? data.TXNAME[index]
: (data.gene_name[index] || data[identifier_col][index]);
if (data.log2FoldChange[index] >= labelFlipThreshold) {
labelXOffset[index] = -7;
labelAlign[index] = "right";
}
}
selectedData.source_index.push(index);
selectedData.owner_id.push(selected_source.id);
@ -909,9 +951,22 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
update_callback.execute(source);
""",
))
y_axis_slider.js_on_change("value", CustomJS(
args=dict(vol_fig=vol_fig, y_axis_slider=y_axis_slider),
code="""
vol_fig.y_range.end = y_axis_slider.value;
""",
))
vol_fig.js_on_event(Reset, CustomJS(
args=dict(vol_fig=vol_fig, y_axis_slider=y_axis_slider),
code="""
y_axis_slider.value = vol_fig.y_range.end;
""",
))
view_toggle.js_on_change("active", CustomJS(
args=dict(
source=source,
vol_fig=vol_fig,
selection_state=selection_state,
highlight_source=highlight_source,
view_toggle=view_toggle,
@ -919,9 +974,17 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
),
code="""
const selectedLabel = source.data.selected_label;
const labelXOffset = source.data.label_x_offset;
const labelAlign = source.data.label_align;
const xRangeStart = vol_fig.x_range.start;
const xRangeEnd = vol_fig.x_range.end;
const xSpan = xRangeEnd - xRangeStart;
const labelFlipThreshold = xRangeEnd - (xSpan * 0.12);
let i = 0;
while (i !== selectedLabel.length) {
selectedLabel[i] = "";
labelXOffset[i] = 7;
labelAlign[i] = "left";
i += 1;
}
source.selected.indices = [];
@ -937,6 +1000,10 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
? source.data.TXNAME[index]
: (source.data.gene_name[index] || \
source.data[identifier_col][index]);
if (source.data.log2FoldChange[index] >= labelFlipThreshold) {
labelXOffset[index] = -7;
labelAlign[index] = "right";
}
highlightData.log2FoldChange.push(source.data.log2FoldChange[index]);
highlightData.neg_log10_padj.push(source.data.neg_log10_padj[index]);
highlightData.mean_expression.push(source.data.mean_expression[index]);
@ -955,6 +1022,8 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
highlight_source.change.emit();
""",
))
vol_fig.x_range.js_on_change("start", update_callback)
vol_fig.x_range.js_on_change("end", update_callback)
gene_select_toggle.js_on_change("active", CustomJS(
args=dict(
source=source,
@ -986,12 +1055,14 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
plot_mode_toggle.js_on_click(CustomJS(
args=dict(
volcano_fig=vol_fig,
y_axis_slider=y_axis_slider,
ma_fig=ma_fig,
plot_mode_toggle=plot_mode_toggle,
),
code="""
const showingVolcano = volcano_fig.visible;
volcano_fig.visible = !showingVolcano;
y_axis_slider.visible = !showingVolcano;
ma_fig.visible = showingVolcano;
plot_mode_toggle.label = showingVolcano
? "Show volcano plot"
@ -1265,7 +1336,13 @@ def volcano(data, fold_threshold=1, p_threshold=0.05):
volcano_ma_plot = BokehPlot()
controls = bokeh_row(
fold_slider, fold_input, p_slider, p_input, sizing_mode="stretch_width")
fold_slider,
fold_input,
p_slider,
p_input,
y_axis_slider,
sizing_mode="stretch_width",
)
toggle_row = bokeh_row(
plot_mode_toggle,
view_toggle,