Oncoprint with GISTIC Copy-Number Levels
Oncoprint graphs offer a visually appealing and informative way to explore genomic alterations across multiple samples in cancer research. They condense complex data into an easily digestible format, highlighting the frequency and type of mutations, copy number variations, and other genomic events within a tumor cohort. This allows researchers to quickly identify patterns and potential therapeutic targets. These graphs typically display samples as rows and genomic alterations as columns, using color-coding to represent different mutation types or copy number changes. Oncoprints are invaluable for identifying frequently mutated genes, characterizing tumor heterogeneity, and guiding personalized cancer medicine strategies. The visualization helps researchers to understand cancer evolution and develop effective treatment plans.
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}
// Create the configuration for the graph
var config = {
"graphType": "Heatmap",
"oncoprintCNA": "data2",
"overlaysThickness": 100,
"oncoprintPresorted": true,
"oncoprintMUT": "data3"
}
// Event used to create graph (optional)
var events = false
// Call the CanvasXpress function to create the graph
var cX = new CanvasXpress("canvasId", data, config, events);
</script>
</body>
</html>
library(canvasXpress)
y=read.table("https://www.canvasxpress.org/data/r/cX-oncoprint6-dat.txt", header=TRUE, sep="\t", quote="", row.names=1, fill=TRUE, check.names=FALSE, stringsAsFactors=FALSE)
y2=read.table("https://www.canvasxpress.org/data/r/cX-oncoprint6-dat2.txt", header=TRUE, sep="\t", quote="", row.names=1, fill=TRUE, check.names=FALSE, stringsAsFactors=FALSE)
y3=read.table("https://www.canvasxpress.org/data/r/cX-oncoprint6-dat3.txt", header=TRUE, sep="\t", quote="", row.names=1, fill=TRUE, check.names=FALSE, stringsAsFactors=FALSE)
canvasXpress(
data=list(y=y, data2=y2, data3=y3),
graphType="Heatmap",
oncoprintCNA="data2",
oncoprintMUT="data3",
oncoprintPresorted=TRUE,
overlaysThickness=100
)
from canvasxpress.canvas import CanvasXpress
from canvasxpress.plot import show_in_browser
if __name__ == "__main__":
# Define the chart with its data and configuration
chart: CanvasXpress = CanvasXpress(
render_to = "oncoprint6",
data = {
"y": {
"vars": ["T30", "T39", "T28", "T05", "T15", "T12", "T20", "T25", "T18", "T29", "T31", "T13", "T10", "T03", "T14", "T21", "T17", "T09", "T02", "T16", "T22", "T06", "T01", "T26", "T07", "T19", "T34", "T35", "T24", "T32", "T11", "T08", "T40", "T41", "T04", "T38", "T36", "T27", "T37", "T23", "T33"],
"smps": ["EGFR", "TP53", "BRCA1", "BRCA2", "MYC", "PTEN", "KRAS", "PIK3CA", "AKT1", "RB1", "MTOR", "CCND1", "CDKN2A", "ZNF140", "ZNF171", "ZNF096", "ZNF042", "ZNF089", "ZNF108", "ZNF051"],
"data": [
[1.45, -0.35, 0.27, -1.67, 0.21, -0.99, 1.55, 1.85, 0.74, 0.52, 0.09, 0.71, -1.57, -0.72, -0.17, 0.84, 0.85, -0.28, -1.55, -0.62],
[-0.4, 2.48, -1.32, -1.03, -0.49, 1.59, 0.79, -1.2, -0.43, -0.57, 0.18, -1.35, -0.81, -0.66, 0.59, 1.46, 0.16, -1.17, -1.29, 0.05],
[2.63, -0.31, -1.54, -1.2, -1.59, -0.75, 1.62, -0.23, 0.09, -0.25, 1.18, 0.2, -1.09, -0.23, 0.69, 1.03, -0.13, -1.13, -0.63, 0.63],
[2.61, -1.32, -0.76, -1.69, 0.42, 1.73, -0.24, -0.82, 0.26, 1.1, 0.48, 0.5, -0.94, -0.17, 1.07, 0.78, -0.35, -0.65, 0.2, 0.3],
[1.61, -1.66, -0.28, 0.55, 0.16, -0.58, -1.2, -1.08, 1.02, 1.37, 0.21, -1.46, -1.62, 0.43, 1.0, 0.33, -0.26, -0.41, 0.33, 0.17],
[1.05, -1.69, 1.15, 1.36, -0.44, -1.65, 0.16, 0.86, 1.5, -0.69, -1.93, -1.06, -0.17, 0.73, 0.56, -0.62, -0.38, 0.52, 0.71, -0.21],
[0.63, -0.64, -0.59, -0.23, -0.06, -1.14, -0.01, 0.24, 0.92, 0.21, -0.59, 0.37, -0.74, 0.04, -0.6, -0.65, 0.38, 1.25, 0.7, -1.19],
[-0.01, -0.01, 2.58, 0.36, -0.32, -2.75, -0.51, -0.71, -0.75, -0.15, -0.14, 0.06, 1.69, -0.34, -0.99, -0.29, 1.15, 0.96, -0.17, -1.27],
[0.39, 1.29, 1.41, 0.66, 0.38, -0.73, 0.22, 0.54, -0.02, -1.47, 1.31, 0.85, 0.42, -0.77, -0.98, -0.26, 1.06, 0.84, -0.42, -0.92],
[1.08, 1.04, 0.51, -0.95, -0.53, 0.19, 0.68, 0.16, -0.41, -0.5, 1.49, 0.61, 0.17, -1.55, -1.13, 0.37, 1.13, 0.44, -0.41, -0.77],
[1.21, 1.1, -0.03, -0.4, 0.22, 1.03, 1.45, -0.91, -1.14, 0.11, 1.43, 1.22, -0.71, -1.3, -0.39, 0.76, 0.78, 0.07, -0.61, 0.17],
[-0.91, 0.09, -1.16, -0.77, 0.48, 2.22, -0.08, -2.48, 0.52, 1.42, 1.01, 0.29, -1.39, -0.62, 0.35, 0.75, -0.38, -0.64, 0.13, 0.98],
[0.5, 0.88, -2.57, -1.42, 1.16, 0.97, -0.38, -1.04, -0.7, 0.61, 1.39, 0.57, -0.39, 0.3, 0.25, -0.21, -0.84, -0.36, 0.95, 1.43],
[-0.32, -2.67, 0.31, 0.57, 0.14, 0.7, -1.07, -1.04, -0.62, 0.65, 0.21, -0.22, -0.27, 0.55, 0.35, -0.68, -0.96, 0.24, 0.98, 0.84],
[-0.65, -2.63, -1.67, 1.06, 0.67, 1.04, -0.77, -0.16, 1.85, 0.32, -0.89, 0.08, 0.59, 1.09, 0.14, -0.98, -1.24, 0.3, 1.2, 0.52],
[-1.45, -2.14, 1.64, 0.56, 0.18, -0.42, 1.21, 2.02, 0.1, -0.78, -0.43, 0.0, 1.3, 1.18, -0.76, -1.48, -0.58, 0.77, 0.97, 0.14],
[-1.22, 0.69, 0.28, -1.03, 0.32, -0.21, 0.79, 1.37, -1.4, -1.16, -0.85, 0.69, 1.03, 0.33, -0.88, -0.92, 0.16, 0.85, -0.15, -0.63],
[-0.52, -1.02, 0.46, -0.25, -0.58, -1.55, 2.28, 0.89, 0.88, 0.14, -0.25, 0.61, 0.89, -0.04, -0.62, -0.06, 0.71, -0.05, -0.66, -0.42],
[0.36, 2.23, 0.29, -1.94, -1.68, -0.84, 1.41, 1.35, 0.7, -2.61, -0.13, 0.76, 0.42, -0.22, 0.03, 0.24, 0.29, -0.55, -0.9, 0.13],
[1.21, 0.58, -1.96, -1.4, -0.49, 1.04, 2.03, -0.24, -1.01, -0.5, 1.09, 0.5, -0.1, -0.65, 0.3, 0.87, 0.13, -0.95, -0.7, 0.22],
[1.14, 0.45, -2.2, -1.05, 1.51, 0.66, 1.67, -1.74, -0.4, 0.39, 0.66, -0.61, -2.29, -0.12, 1.11, 1.09, -0.2, -1.59, -0.73, 0.76],
[1.22, 0.13, -0.78, -2.21, -1.11, 0.45, -0.14, -0.3, 0.47, 0.48, -0.09, -1.07, -0.87, 0.58, 1.58, 0.32, -1.0, -1.17, -0.01, 0.95],
[0.89, -0.08, -1.49, -0.04, 1.74, -0.69, -0.47, 0.25, 0.74, 2.07, -0.43, 0.08, -0.37, 0.58, 0.99, -0.01, -0.85, -0.39, 0.59, 0.12],
[-0.2, -0.58, -0.63, 1.99, 1.62, -0.56, 0.27, 0.97, 1.96, 0.67, 0.61, -2.81, -0.27, 0.84, 0.61, -0.24, -0.28, -0.09, 0.24, -0.37],
[-0.56, 0.55, 0.92, -0.26, 0.01, -1.4, 0.07, 0.98, 1.42, -0.94, -1.22, -0.15, 0.33, 0.68, 0.09, -0.14, -0.02, 0.63, 0.13, -0.85],
[0.08, 0.64, 0.98, -0.9, -0.95, -0.55, 0.08, 0.02, -0.13, -1.78, -0.06, 0.08, 0.62, 0.2, -0.87, -0.27, 0.86, 0.96, -0.2, -1.04],
[-0.78, 0.75, 1.21, 0.11, -2.26, 0.72, 1.4, 0.63, 0.04, -0.41, -1.17, 2.13, -0.07, -0.93, -0.86, 0.44, 1.46, 0.89, -1.08, -1.37],
[0.51, 1.18, 1.0, -0.14, -0.49, -0.33, 0.43, 0.18, -0.35, 0.03, 0.44, 0.62, -0.41, -1.21, -0.45, 1.12, 1.02, -0.01, -1.05, -0.69],
[0.49, 1.16, -0.05, 0.59, -0.34, 0.43, 0.36, 0.92, -2.3, 0.15, 1.13, 0.61, -0.74, -1.05, -0.39, 0.9, 0.76, -0.27, -0.58, 0.19],
[1.5, 0.16, -0.44, -0.94, 0.6, 0.23, -0.58, -1.34, 0.65, 0.88, 0.1, 0.99, -2.69, -1.06, 0.24, 0.84, 0.27, -0.24, -0.36, 0.36],
[0.22, -0.4, -1.19, -0.87, 2.01, -0.98, -0.96, -2.58, -0.02, 1.34, 0.63, 0.12, -1.0, -0.22, 0.6, 0.42, -0.74, -0.43, 0.55, 0.8],
[-0.12, -0.83, 0.41, 1.26, 1.13, -1.22, -0.45, 0.51, 0.62, 0.12, 0.84, -0.53, 1.07, 0.57, 0.58, -0.74, -0.83, 0.27, 1.28, 0.82],
[0.1, -2.77, -1.54, 2.45, 2.35, -0.19, 0.5, 0.05, 1.07, 1.05, -0.23, -0.15, 1.36, 0.45, -0.35, -1.13, -0.51, 1.01, 1.59, -0.03],
[-2.02, 0.23, 1.72, -0.02, 0.67, 0.46, 0.61, 0.18, 0.43, -1.46, 0.29, -0.06, -0.4, 0.53, -0.74, -1.12, 0.1, 0.9, 0.85, -0.31],
[-0.52, -1.65, -0.45, -0.28, -0.34, -0.5, -0.41, 0.71, 1.41, -1.21, -0.7, 0.73, 1.31, 0.31, -0.9, -1.26, 0.16, 0.97, 0.42, -0.35],
[-1.19, -1.47, 0.31, -0.17, -0.51, -0.46, 1.09, 0.24, -0.92, -1.3, -0.12, 1.31, 1.27, -0.58, -1.25, -0.49, 0.59, 0.63, -0.01, -0.61],
[-0.23, -0.92, 0.0, -0.67, -0.29, 0.41, 0.99, -1.26, 0.13, -0.94, -0.1, 1.52, 0.31, -0.65, -0.57, 0.31, 0.64, -0.52, -0.78, 0.06],
[0.65, -0.75, -0.46, -0.19, -0.33, 0.42, -0.25, -1.55, -1.02, -0.83, 0.41, 0.61, -0.12, -0.35, 0.35, 0.27, -0.26, -1.0, -0.55, 0.85],
[1.24, 0.39, -1.39, -2.48, 1.64, 1.34, 2.05, -0.37, 0.28, -0.05, -0.79, 0.07, -0.32, 0.31, 0.62, 0.44, -0.69, -1.12, 0.01, 0.86],
[0.79, 0.13, -1.34, 0.76, 1.5, 1.16, 1.05, -0.71, -0.12, 0.54, 0.23, -0.45, -0.74, 0.52, 1.16, 0.27, -0.97, -0.8, 0.07, 1.07],
[0.56, -0.68, -2.13, 0.22, -0.91, -1.24, 0.83, -0.08, 0.78, 0.75, -0.83, -1.26, -0.21, 1.21, 1.26, -0.03, -1.45, -0.72, 0.57, 0.83]
],
"data2": [
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"data3": [
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]
}
},
config = {
"graphType": "Heatmap",
"oncoprintCNA": "data2",
"overlaysThickness": 100,
"oncoprintPresorted": True,
"oncoprintMUT": "data3"
},
width = 900,
height = 650
)
# Display the chart in its own Web page
show_in_browser(chart)
Run this notebook:
from canvasxpress.canvas import CanvasXpress
from canvasxpress.plot import graph
graph(
CanvasXpress(
render_to = "oncoprint6",
data = {
"y": {
"vars": ["T30", "T39", "T28", "T05", "T15", "T12", "T20", "T25", "T18", "T29", "T31", "T13", "T10", "T03", "T14", "T21", "T17", "T09", "T02", "T16", "T22", "T06", "T01", "T26", "T07", "T19", "T34", "T35", "T24", "T32", "T11", "T08", "T40", "T41", "T04", "T38", "T36", "T27", "T37", "T23", "T33"],
"smps": ["EGFR", "TP53", "BRCA1", "BRCA2", "MYC", "PTEN", "KRAS", "PIK3CA", "AKT1", "RB1", "MTOR", "CCND1", "CDKN2A", "ZNF140", "ZNF171", "ZNF096", "ZNF042", "ZNF089", "ZNF108", "ZNF051"],
"data": [
[1.45, -0.35, 0.27, -1.67, 0.21, -0.99, 1.55, 1.85, 0.74, 0.52, 0.09, 0.71, -1.57, -0.72, -0.17, 0.84, 0.85, -0.28, -1.55, -0.62],
[-0.4, 2.48, -1.32, -1.03, -0.49, 1.59, 0.79, -1.2, -0.43, -0.57, 0.18, -1.35, -0.81, -0.66, 0.59, 1.46, 0.16, -1.17, -1.29, 0.05],
[2.63, -0.31, -1.54, -1.2, -1.59, -0.75, 1.62, -0.23, 0.09, -0.25, 1.18, 0.2, -1.09, -0.23, 0.69, 1.03, -0.13, -1.13, -0.63, 0.63],
[2.61, -1.32, -0.76, -1.69, 0.42, 1.73, -0.24, -0.82, 0.26, 1.1, 0.48, 0.5, -0.94, -0.17, 1.07, 0.78, -0.35, -0.65, 0.2, 0.3],
[1.61, -1.66, -0.28, 0.55, 0.16, -0.58, -1.2, -1.08, 1.02, 1.37, 0.21, -1.46, -1.62, 0.43, 1.0, 0.33, -0.26, -0.41, 0.33, 0.17],
[1.05, -1.69, 1.15, 1.36, -0.44, -1.65, 0.16, 0.86, 1.5, -0.69, -1.93, -1.06, -0.17, 0.73, 0.56, -0.62, -0.38, 0.52, 0.71, -0.21],
[0.63, -0.64, -0.59, -0.23, -0.06, -1.14, -0.01, 0.24, 0.92, 0.21, -0.59, 0.37, -0.74, 0.04, -0.6, -0.65, 0.38, 1.25, 0.7, -1.19],
[-0.01, -0.01, 2.58, 0.36, -0.32, -2.75, -0.51, -0.71, -0.75, -0.15, -0.14, 0.06, 1.69, -0.34, -0.99, -0.29, 1.15, 0.96, -0.17, -1.27],
[0.39, 1.29, 1.41, 0.66, 0.38, -0.73, 0.22, 0.54, -0.02, -1.47, 1.31, 0.85, 0.42, -0.77, -0.98, -0.26, 1.06, 0.84, -0.42, -0.92],
[1.08, 1.04, 0.51, -0.95, -0.53, 0.19, 0.68, 0.16, -0.41, -0.5, 1.49, 0.61, 0.17, -1.55, -1.13, 0.37, 1.13, 0.44, -0.41, -0.77],
[1.21, 1.1, -0.03, -0.4, 0.22, 1.03, 1.45, -0.91, -1.14, 0.11, 1.43, 1.22, -0.71, -1.3, -0.39, 0.76, 0.78, 0.07, -0.61, 0.17],
[-0.91, 0.09, -1.16, -0.77, 0.48, 2.22, -0.08, -2.48, 0.52, 1.42, 1.01, 0.29, -1.39, -0.62, 0.35, 0.75, -0.38, -0.64, 0.13, 0.98],
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