Scatter Plot of Gene-Gene Correlation
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A correlation scatter plot is a type of chart used to display the relationship between two variables.
Input
The first row is ID, the second and third rows are genes, separated by \t.
Output
1. Chart Purpose
This chart aims to visualize and analyze whether there is a statistically significant association between the expression levels of two genes (the x-axis represents [Gene 1 name] and the y-axis represents [Gene 2 name]) across all samples.
2. How to Interpret This Chart
Central Scatter Plot:
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Each point in the plot represents a sample.
-
The distribution trend of the points reveals the relationship between the expression levels of the two genes:
-
If the points tend to cluster from the bottom-left to the top-right, it indicates a positive correlation.
-
If the points trend from the top-left to the bottom-right, it suggests a negative correlation.
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The statistical values provided are:
-
"R": Represents the Spearman correlation coefficient, measuring the strength of the correlation.
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"p": Represents the p-value, used to determine whether the correlation is statistically significant (typically, p < 0.05 is considered significant).
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Top and Right Density Plots:
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Top plot (orange): Displays the distribution of the x-axis gene's expression levels across all samples. A higher peak indicates that more samples are concentrated at that expression level.
-
Right plot (blue): Shows the distribution of the y-axis gene's expression levels across all samples.
A correlation scatter plot is a type of chart used to display the relationship between two variables.
Input
The first row is ID, the second and third rows are genes, separated by \t.
Output
1. Chart Purpose
This chart aims to visualize and analyze whether there is a statistically significant association between the expression levels of two genes (the x-axis represents [Gene 1 name] and the y-axis represents [Gene 2 name]) across all samples.
2. How to Interpret This Chart
Central Scatter Plot:
-
Each point in the plot represents a sample.
-
The distribution trend of the points reveals the relationship between the expression levels of the two genes:
-
If the points tend to cluster from the bottom-left to the top-right, it indicates a positive correlation.
-
If the points trend from the top-left to the bottom-right, it suggests a negative correlation.
-
-
The statistical values provided are:
-
"R": Represents the Spearman correlation coefficient, measuring the strength of the correlation.
-
"p": Represents the p-value, used to determine whether the correlation is statistically significant (typically, p < 0.05 is considered significant).
-
Top and Right Density Plots:
-
Top plot (orange): Displays the distribution of the x-axis gene's expression levels across all samples. A higher peak indicates that more samples are concentrated at that expression level.
-
Right plot (blue): Shows the distribution of the y-axis gene's expression levels across all samples.