output_backend="webgl")
cr = p.circle(x='tsne_x', y='tsne_y', color=cls_color_mapper, source=source)
cr.selection_glyph = Circle(fill_color=cls_color_mapper,
line_color=cls_color_mapper)
cr.nonselection_glyph = Circle(fill_color=cls_color_mapper,
line_color=cls_color_mapper,
fill_alpha=0.05,
line_alpha=0.05)
color_bar = ColorBar(color_mapper=LinearColorMapper(palette="Viridis256",
low=1,
high=10),
label_standoff=12,
border_line_color=None,
location=(0, 0))
p.add_layout(color_bar, 'right')
color_bar.visible = False
if type(cls_color_mapper['transform']) is LinearColorMapper:
color_bar.color_mapper = cls_color_mapper['transform']
# p.add_layout(color_bar, 'right')
color_bar.visible = True
# Define widgets
hover_tip_tool = HoverTool(tooltips=generate_tooltip_html(),
show_arrow=False,
renderers=[cr])
wheel_zoom_tool = WheelZoomTool()
file_select_dropdown = Dropdown(label="Data file",
button_type="warning",
height_policy='min',
menu=[('refresh list', 'refresh_list'), None])
update_file_list()
color_class_select = Select(title="Colored by:",
def Mosaic_Plot(clone_df,
png=None,
title="",
top_clones=5000,
count_col="Clustered",
vgene_col="VGene",
jgene_col="JGene",
isotype_col="Isotype",
vshm_col="V_SHM",
jshm_col="J_SHM",
vgene_colors=vgene_colors,
vfamily_colors=vfamily_colors,
jgene_colors=jgene_colors,
isotype_colors=isotype_colors,
line_width=0.3,
figsize=(600, 600),
hover_tooltip=True):
figure_params = {
"plot_width": figsize[0],
"plot_height": figsize[1],
#"sizing_mode": "scale_both",
"x_range": Range1d(-0.1, 1.1, bounds=(-1.0, 2.0)),
"y_range": Range1d(-0.1, 1.1, bounds=(-1.0, 2.0)),
#"outline_line_alpha": 0.0,
"title": title,
"tools": "pan, wheel_zoom, box_zoom, save, reset, help",
"active_scroll": "wheel_zoom",
"toolbar_location": "right"
}
plot = figure(**figure_params)
plot.grid.visible = False
plot.axis.visible = False
hover_tooltips = [("Clone ID", "@CloneID")]
info_cols = [count_col]
if vgene_col is not None:
info_cols.append(vgene_col)
hover_tooltips.append(("V Gene", "@" + vgene_col))
if jgene_col is not None:
info_cols.append(jgene_col)
hover_tooltips.append(("J Gene", "@" + jgene_col))
if isotype_col is not None:
info_cols.append(isotype_col)
hover_tooltips.append(("Isotype", "@" + isotype_col))
if vshm_col is not None:
info_cols.append(vshm_col)
hover_tooltips.append(("V Gene SHM", "@" + vshm_col + "{(0.00%)}"))
if jshm_col is not None:
info_cols.append(jshm_col)
hover_tooltips.append(("J Gene SHM", "@" + jshm_col + "{(0.00%)}"))
if hover_tooltip:
hover_tool = HoverTool(point_policy="snap_to_data",
tooltips=hover_tooltips)
plot.add_tools(hover_tool)
mosaic_df = clone_df[info_cols]
mosaic_df = mosaic_df.sort_values([count_col], ascending=[False])
if top_clones:
mosaic_df = mosaic_df.head(top_clones)
total_area = float(mosaic_df[count_col].sum())
mosaic_df["Clone_Frequencies"] = mosaic_df[count_col].astype(
float) / total_area
hover_tooltips.append(("Clone Frequency", "@Clone_Frequencies{(0.00%)}"))
mosaic_rects = squarify(mosaic_df["Clone_Frequencies"].tolist(), 0.0, 0.0,
1.0, 1.0)
#Add half width/height to x/y position for center points
mosaic_df["x"] = [rect["x"] + rect["dx"] / 2.0 for rect in mosaic_rects]
mosaic_df["y"] = [rect["y"] + rect["dy"] / 2.0 for rect in mosaic_rects]
mosaic_df["width"] = [rect["dx"] for rect in mosaic_rects]
mosaic_df["height"] = [rect["dy"] for rect in mosaic_rects]
#By default there is no legend text, since colors are alternating and non-informative
mosaic_df["legend"] = ""
mosaic_df["Empty_Legend"] = ""
alternating_colors = [
RGB(102, 194, 165),
RGB(252, 141, 98),
RGB(141, 160, 203)
]
alt2_color_cycle = cycle(alternating_colors[0:2])
alt3_color_cycle = cycle(alternating_colors)
mosaic_df["alternating2_colors"] = [
next(alt2_color_cycle) for _ in mosaic_rects
]
mosaic_df["alternating3_colors"] = [
next(alt3_color_cycle) for _ in mosaic_rects
]
#Default color scheme is alternating 3 colors
mosaic_df["fill_color"] = mosaic_df["alternating3_colors"]
#Set up various mosaic coloring options and associated legends
color_select_options = ["Alternating (2)", "Alternating (3)"]
if vgene_col in mosaic_df.columns:
mosaic_df["vgene_colors"] = mosaic_df[vgene_col].map(vgene_colors)
vfamilies = mosaic_df[vgene_col].str.split("-").str[0]
mosaic_df["vfamily_colors"] = vfamilies.map(vfamily_colors)
color_select_options.append("V Gene")
color_select_options.append("V Family")
mosaic_df["VGene_Legend"] = mosaic_df[vgene_col]
mosaic_df["VFamily_Legend"] = mosaic_df[vgene_col].str.split(
"-").str[0]
if jgene_col in mosaic_df.columns:
mosaic_df["jgene_colors"] = mosaic_df[jgene_col].map(jgene_colors)
color_select_options.append("J Gene")
mosaic_df["JGene_Legend"] = mosaic_df[jgene_col]
if isotype_col in mosaic_df.columns:
mosaic_df["isotype_colors"] = mosaic_df[isotype_col].map(
isotype_colors)
color_select_options.append("Isotype")
mosaic_df["Isotype_Legend"] = mosaic_df[isotype_col]
#Using viridis as a quantitative heatmap color scheme for SHM values
#The SHM values are binned into 180 groups; viridis in >180 bins uses some values twice, which pandas.cut can't use
shm_viridis = list(viridis(180))
colorbar_tick_formatter = NumeralTickFormatter(format="0.00%")
if vshm_col in mosaic_df.columns:
vshm_min = mosaic_df[vshm_col].min()
vshm_max = mosaic_df[vshm_col].max()
#Use pandas.cut to bin the V gene SHM values into the heatmap colors
mosaic_df["vshm_colors"] = pandas.cut(mosaic_df[vshm_col],
bins=180,
labels=shm_viridis)
color_select_options.append("V Gene SHM")
vshm_color_mapper = LinearColorMapper(palette=shm_viridis,
low=vshm_min,
high=vshm_max)
vshm_ticks = FixedTicker(ticks=numpy.linspace(vshm_min, vshm_max, 8))
vshm_colorbar = ColorBar(color_mapper=vshm_color_mapper,
location=(0, 0),
name="vshm_colorbar",
label_standoff=12,
formatter=colorbar_tick_formatter,
ticker=vshm_ticks)
plot.add_layout(vshm_colorbar, "right")
if jshm_col in mosaic_df.columns:
jshm_min = mosaic_df[jshm_col].min()
jshm_max = mosaic_df[jshm_col].max()
#Use pandas.cut to bin the J gene SHM values into the heatmap colors
mosaic_df["jshm_colors"] = pandas.cut(mosaic_df[jshm_col],
bins=180,
labels=shm_viridis)
color_select_options.append("J Gene SHM")
jshm_color_mapper = LinearColorMapper(palette=shm_viridis,
low=jshm_min,
high=jshm_max)
jshm_ticks = FixedTicker(ticks=numpy.linspace(jshm_min, jshm_max, 8))
jshm_colorbar = ColorBar(color_mapper=jshm_color_mapper,
location=(0, 0),
name="jshm_colorbar",
label_standoff=12,
formatter=colorbar_tick_formatter,
ticker=jshm_ticks)
plot.add_layout(jshm_colorbar, "right")
mosaic_source = ColumnDataSource(mosaic_df)
plot.rect(x="x",
y="y",
width="width",
height="height",
fill_color="fill_color",
legend="legend",
line_color="black",
line_width=line_width,
source=mosaic_source)
#By default, the plot legend and ColorBar should be turned off (since the color is repeating and uninformative)
plot.legend[0].visible = False
vshm_colorbar = plot.select("vshm_colorbar")[0]
jshm_colorbar = plot.select("jshm_colorbar")[0]
vshm_colorbar.visible = False
jshm_colorbar.visible = False
if png is not None:
export_png(plot, png)
change_args = {
"source": mosaic_source,
"legend_obj": plot.legend[0],
"vshm_colorbar_obj": vshm_colorbar,
"jshm_colorbar_obj": jshm_colorbar
}
change_rect_color = CustomJS(args=change_args,
code="""
var selection = cb_obj.value.toLowerCase();
var new_color_array;
var new_legend_array;
if(selection.indexOf("v gene shm") !== -1) {
new_color_array = source.data["vshm_colors"];
new_legend_array = source.data["Empty_Legend"];
legend_obj.visible = false;
vshm_colorbar_obj.visible = true;
jshm_colorbar_obj.visible = false;
} else if(selection.indexOf("j gene shm") !== -1) {
new_color_array = source.data["jshm_colors"];
new_legend_array = source.data["Empty_Legend"];
legend_obj.visible = false;
vshm_colorbar_obj.visible = false;
jshm_colorbar_obj.visible = true;
} else if(selection.indexOf("v gene") !== -1) {
new_color_array = source.data["vgene_colors"];
new_legend_array = source.data["VGene_Legend"];
legend_obj.visible = true;
vshm_colorbar_obj.visible = false;
jshm_colorbar_obj.visible = false;
} else if(selection.indexOf("v family") !== -1) {
new_color_array = source.data["vfamily_colors"];
new_legend_array = source.data["VFamily_Legend"];
legend_obj.visible = true;
vshm_colorbar_obj.visible = false;
jshm_colorbar_obj.visible = false;
} else if(selection.indexOf("j gene") !== -1) {
new_color_array = source.data["jgene_colors"];
new_legend_array = source.data["JGene_Legend"];
legend_obj.visible = true;
vshm_colorbar_obj.visible = false;
jshm_colorbar_obj.visible = false;
} else if(selection.indexOf("isotype") !== -1) {
new_color_array = source.data["isotype_colors"];
new_legend_array = source.data["Isotype_Legend"];
legend_obj.visible = true;
vshm_colorbar_obj.visible = false;
jshm_colorbar_obj.visible = false;
} else if(selection.indexOf("2") !== -1) {
new_color_array = source.data["alternating2_colors"];
new_legend_array = source.data["Empty_Legend"];
legend_obj.visible = false;
vshm_colorbar_obj.visible = false;
jshm_colorbar_obj.visible = false;
} else {
new_color_array = source.data["alternating3_colors"];
new_legend_array = source.data["Empty_Legend"];
legend_obj.visible = false;
vshm_colorbar_obj.visible = false;
jshm_colorbar_obj.visible = false;
}
var fill_color = source.data["fill_color"];
var legend = source.data["legend"];
for(idx = 0; idx < fill_color.length; idx++) {
fill_color[idx] = new_color_array[idx];
legend[idx] = new_legend_array[idx];
}
source.change.emit();
""")
patch_coloring_select = Select(title="Color by:",
options=color_select_options,
value="Alternating (3)",
callback=change_rect_color)
plot_layout = column(patch_coloring_select, plot)
return plot_layout
