The miRNA section visualizes the correlation between user-selected sRNA and immune infiltrates over 32 cancer types.
In this section, you are supposed to receive a heatmap and its corresponding table with statistical values. Please follow these steps:
Fill in the name of a miRNA.
Select at least one immune infiltrates you are interested in from the drop-down list.
Choose whether to select 'Purity Adjustment' or not (the default option is selected).
Click the 'Submit' button to submit your data.
Note: Since most immune cell types negatively correlate with tumor purity, tumor purity is considered a main confounding factor in the following analysis. Therefore, we recommend selecting the 'Purity Adjustment' option, for this option will utilize partial Spearman's correlation to perform a more accurate association analysis.
Association heatmap of miRNA and immune infiltrates
The heatmap illustrates the correlation across diverse cancer types between user-selected miRNA and immune infiltrates calculated by different methods. Each cell's color in the heatmap represents the correlation between variables (red for positive, blue for negative, and grey for non-correlated). Additional information includes the p-value, correlation coefficient, and calculated method.
On the top of the plot is the cancer type. You can hover the mouse on a specific cancer type to view its full name and corresponding tissue. The immune infiltrates and methods are on the left of the heatmap; you can view the corresponding cell types by hovering the mouse over the side color bar on the right.
Hover on a heatmap cell to view detailed information.
Click on a distinct heatmap cell, and the corresponding correlation plots will pop up.
(Note: If the data is not linear, there might be a disparity between the correlation coefficient (Rho) and the slope of the line.)
The table provides the statistical values of user-selected miRNA and immune subtypes of different tools, including p-value and correlation coefficients.
Click on a specific row, and the corresponding correlation plots will pop up.
(Note: If the data is not linear, there might be a disparity between the correlation coefficient (Rho) and the slope of the line.)
The Immune infiltration section visualizes the correlation between user-selected immune infiltrates and miRNAs over 32 cancer types.
In this section, you are supposed to receive a heatmap and its corresponding table with statistical values. Please follow these steps:
Select an immune infiltrate from the drop-down list.
Select a cell type according to this immune infiltrate from the drop-down list.
Choose whether to select 'Purity Adjustment' or not (the default option is selected).
Click the 'Submit' button to submit your data.
Note: Since most immune cell types negatively correlate with tumor purity, tumor purity is considered a main confounding factor in the following analysis. Therefore, we recommend selecting the 'Purity Adjustment' option, for this option will utilize partial Spearman's correlation to perform a more accurate association analysis.
Association heatmap of immune cell infiltration and miRNAs
The heatmap illustrates the correlation between user-selected immune infiltrate and miRNA across 32 cancer types. Each cell's color in the heatmap represents the correlation between variables (red for positive, blue for negative, and grey for non-correlated). Additional information includes the p-value, correlation coefficient, and calculated method.
On the top of the plot is the cancer type. You can hover the mouse on a specific cancer type to view its full name and corresponding tissue. On the left of the heatmap is the 30 microRNAs that are correlated with the most cancer types.
Hover on a heatmap cell to view detailed information.
Click on a distinct heatmap cell, and the corresponding correlation plots will pop up.
(Note: If the data is not linear, there might be a disparity between the correlation coefficient (Rho) and the slope of the line.)
The table provides the statistical values of user-selected immune infiltrate and miRNAs across 32 cancer types, including p-value and correlation coefficients.
(Note: The miRNA listed in this table must be associated with more than two cancer types.)
Click on a specific row, and the corresponding correlation plots will pop up.
(Note: If the data is not linear, there might be a disparity between the correlation coefficient (Rho) and the slope of the line.)
The Cancer section visualizes the correlation between user-selected immune infiltrates of a specific cancer type and miRNAs.
In this section, you are supposed to receive a heatmap and its corresponding table with statistical values. Please follow these steps:
Select a cancer dataset from the drop-down list.
Select at least one immune infiltrates you are interested in from the drop-down list.
Choose whether to select 'Purity Adjustment' or not (the default option is selected).
Click the 'Submit' button to submit your data.
Note: Since most immune cell types negatively correlate with tumor purity, tumor purity is considered a main confounding factor in the following analysis. Therefore, we recommend selecting the 'Purity Adjustment' option, for this option will utilize partial Spearman's correlation to perform a more accurate association analysis.
Association heatmap of immune cell infiltration and miRNAs in a specific cancer type
The heatmap illustrates the correlation between user-selected immune infiltrate in a specific selected cancer type and miRNAs. Each cell's color in the heatmap represents the correlation between variables (red for positive, blue for negative, and grey for non-correlated). Additional information includes the p-value, correlation coefficient, and calculated method.
On the top of the heatmap is the 30 sRNAs that are correlated with the most cancer types. The immune infiltrates and methods are on the left of the heatmap; you can view the corresponding cell types by hovering the mouse over the side color bar on the right.
Hover on a heatmap cell to view detailed information.
Click on a distinct heatmap cell, and the corresponding correlation plots will pop up.
(Note: If the data is not linear, there might be a disparity between the correlation coefficient (Rho) and the slope of the line.)
The table provides the statistical values of user-selected sRNA and immune subtypes of different tools, including p-value and correlation coefficients.
(Note: The sRNA listed in this table must be associated with more than two cancer types.)
Click on a specific row, and the corresponding correlation plots will pop up.
(Note: If the data is not linear, there might be a disparity between the correlation coefficient (Rho) and the slope of the line.)