Heatmap Plot
The heat map (also called a clustergram) is a graphic representation of the unsupervised hierarchical clustering of target (gene) expression across all samples or biogroups in the study. In the plot, the targets and samples are arranged according to the similarity of their gene expression. The software uses either Pearson's correlation or Euclidean distance to calculate distances between samples and assays for hierarchical clustering based on their ΔCT values.
In the hierarchical clustering calculation, each sample/assay data point is represented as a node in the plot that is successively joined to nodes nearest to it by branches until all points are combined into a single cluster. The distance between the clusters (the inter-cluster distance) is defined by the linkage method, which the software can calculate three different ways (single, complete, or average). For more information on hierarchical clustering and linkage methods, see D'haeseleer P (2005) How does gene expression clustering work? Nat Biotechnol 23(12):1499-1501. .
Note: If you have configured your study with biogroups, the software displays the Biogroup/Sample switch that allows you to organize the results in the Heatmap Plot. If displayed, select Biogroup to group the results by biogroup or select Sample to compare the samples individually.
View Settings
The software provides multiple options for configuring the Heatmap Plot for review. To change the view settings, click
View
, then select the appropriate view options for the heatmap plot:
Option |
Settings |
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Select the method to use for the sample-assay distance calculation for hierarchical clustering:
Note: The Euclidean Distance method of distance calculation is sensitive to scaling and differences in average expression level, whereas the Pearson's Correlation method is not. |
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Select the linkage method to use for the hierarchical clustering calculations:
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Select the type of Heatmap in which you want the software to display the results of the hierarchical clustering calculations. For each map type, the ΔCT value of the neutral/middle expression level (mean or median) is set such that red indicates an increase with a ΔCT value below the middle level, and green indicates a decrease, with a ΔCT value above the middle level. Note: The color indicators (Red/Green by default) are determined by the Color Scheme setting.
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Select a color scheme for the software to display the results of the hierarchical clustering calculations: Red/Green, Red/ Blue, or Green/Orange color schemes. |
Heatmap tooltips
When mousing over the Heatmap Plot, the software displays in a tooltip window the ΔCT and ΔCT + global control mean (or global median if global normalization is selected in the analysis settings) for the given sample/target combination. The global control mean is the mean CT value of all selected endogenous controls in the study. The global median is the median value used if global normalization was in use. This value (global control mean or global median) is added on to the ΔCT to better approximate the original CT (a rough estimate of expression level) calculated for each sample and given assay before normalization.
Results Details table
Below the Heatmap Plot is the Results Details table, showing the following information: