Within computational biology, an MA plot is an application of a Bland–Altman plot for visual representation of genomic data. The plot visualizes the differences between measurements taken in two samples, by transforming the data onto M (log ratio) and A (mean average) scales, then plotting these values.

MA plots are a widely used way to visualize genomic data. The M represents the difference between two conditions (fold-change), while the A represents the average intensity of the expression. Both values take on a \(\log_{2}\) transformation.

What is MA plot?¶ MA plot shows the log average (A) on the -axis and the log ratio (M) on the -axis. Here, M stands for minus because . Similar plots are Bland-Altman plot, Tukey mean-difference plot, mean-difference plot, or MD plot. This type of plot is good to show the data distribution between two individuals or two groups. Examples include:

Make MA-plot which is a scatter plot of log2 fold changes (M, on the y-axis) versus the average expression signal (A, on the x-axis). M = log2(x/y) and A = (log2(x) + log2(y))/2 = log2(xy)*1/2, where x and y are respectively the mean of the two groups being compared.

MA plots are commonly used to represent log fold-change versus mean expression between two treatments . This is visually displayed as a scatter plot with base-2 log fold-change along the y-axis and normalized mean expression along the x-axis.

2022年2月6日 · What is MA plot? MA plot is a 2-dimensional (2D) scatter plot used for visualizing gene expression datasets; MA plot visualize and identify gene expression changes from two different conditions (e.g. normal vs. treated) in terms of log fold change (M) on Y-axis and log of the mean of normalized expression counts of two conditions on X-axis.

MA plots showing average logarithmically transformed counts per million (CPM) versus the log 2 fold change for pairwise comparisons between the Transplant 2H versus Naive (top row), Transplant 24H versus Naive (middle row), and Transplant 24H versus Transplant 2H …

Plot representations are simple but very helpful tools to detect artifacts or other trends in microarray data. The most basic plots present the two channel intensities versus each other on a linear or log scale (Fig. 7.5A and B).

MA Plot. The MA plot is a visualisation that plots the log-fold-change between experimental groups (M) against the average expression across all the samples (A) for each gene. The Glimma MA plot contains two main components: a plot of summary statistics across all genes that have been tested, and

In the context of microarray expression data, MA plots are used to examine the intensity measurements resulting from two channels. These channels can be drawn from either: Two or more chips from a one-color platform. (We can call the intensity measurements from chip 1 R, and those from chip 2 G.)