MA plot

The MA plot is a scatter plot rotated by $ 45^{\circ}$. For two samples of expression values it plots for each gene the difference in expression against the mean expression level. MA plots are often used for quality control, in particular, to assess whether normalization and/or transformation is required.

You can create an MA plot comparing two samples by going to:

        Tools | Microarray Analysis (Image expressionfolder)| General Plots (Image general_plots_folder_closed_16_n_p) | Create MA Plot (Image ma_plot)

In the first wizard step, select the case expression data ( (Image array), (Image rnaseq) or (Image rnaseqtrack_16_h_p) ), and in the second wizard step, select the control data.

In the following wizard step (figure 34.56), specify the values types to be used for creating the MA plot (see Selecting transformed and normalized values for analysis).

Image ma_step2
Figure 34.56: Selecting which values the MA plot should be based on.

Click on Finish to launch the analysis.

Viewing MA plots

The resulting plot is shown in figure 34.57.

Image ma_before_transform_web
Figure 34.57: MA plot based on original expression values.

The X axis shows the mean expression level of a feature on the two samples and the Y axis shows the difference in expression levels for a feature on the two samples. From the plot shown in figure 34.57 it is clear that the variance increases with the mean. With an MA plot like this, you will often choose to transform the expression values.

Figure 34.58 shows the same two samples where the MA plot has been created using log2 transformed values.

Image ma_after_transform_web
Figure 34.58: MA plot based on transformed expression values.

A more symmetric and even spread indicates that the dependence of the variance on the mean is not as strong as it was before transformation.

In the Side Panel to the left, there is a number of options to adjust the view. Under Graph preferences, you can adjust the general properties of the plot.

Below the general preferences, you find the Dot properties preferences, where you can adjust coloring and appearance of the dots:

Note that if you wish to use the same settings next time you open a scatter plot, you need to save the Side Panel settings.