MA Plot for Differential Expression in Python, R, Julia and JavaScript

Source code in 15 libraries — Python: Altair, Bokeh, lets-plot, Matplotlib, Plotly, plotnine, Pygal, Seaborn; R: ggplot2; Julia: Makie.jl; JavaScript: Chart.js, D3.js, Apache ECharts, Highcharts, MUI X Charts.

An MA plot (M-versus-A plot) visualizes the relationship between log fold change (M) and mean average expression (A) when comparing two experimental conditions. Each point represents a gene or feature, with significantly differentially expressed genes highlighted. This plot is a standard diagnostic tool in RNA-seq and microarray analysis for assessing differential expression results and detecting systematic expression-dependent bias.

Renders

• Full-resolution render, light theme
• Full-resolution render, dark theme
• Interactive version, light theme
• Interactive version, dark theme

Preview render from the lets-plot implementation.

Implementations

• MA Plot for Differential Expression in Altair (Python)
• MA Plot for Differential Expression in Bokeh (Python)
• MA Plot for Differential Expression in lets-plot (Python)
• MA Plot for Differential Expression in Matplotlib (Python)
• MA Plot for Differential Expression in Plotly (Python)
• MA Plot for Differential Expression in plotnine (Python)
• MA Plot for Differential Expression in Pygal (Python)
• MA Plot for Differential Expression in Seaborn (Python)
• MA Plot for Differential Expression in ggplot2 (R)
• MA Plot for Differential Expression in Makie.jl (Julia)
• MA Plot for Differential Expression in Chart.js (JavaScript)
• MA Plot for Differential Expression in D3.js (JavaScript)
• MA Plot for Differential Expression in Apache ECharts (JavaScript)
• MA Plot for Differential Expression in Highcharts (JavaScript)
• MA Plot for Differential Expression in MUI X Charts (JavaScript)