Ggplot2 geom treemap rendering

ggplot2-geom-treemap-rendering

Summary

Render hierarchical ion filtering results as a treemap visualization using ggplot2's geom_treemap() and geom_treemap_text() layers, scaled by ion counts and annotated with filter status labels and percentages. This skill transforms aggregated qc_summary() data into a publication-ready treemap that communicates the distribution and relative abundance of ions across filter outcome categories.

When to use

After running qc_summary() on a filtered mpactr object and aggregating ion counts by filter status category (passed/failed). Use this skill when you need to communicate the proportional breakdown of ions retained vs. removed by filtering, and when a compact, area-encoded visualization is preferred over bar charts for showing multiple hierarchical dimensions (status, count, percentage) simultaneously.

When NOT to use

• Input contains only a single filter status category (treemap loses hierarchical meaning with one rectangle).
• Ion count data is not pre-aggregated by status; raw feature-level data will produce an uninterpretable treemap with too many small tiles.
• Audience requires precise numerical comparison across many status categories; bar charts or tables are more readable than area encoding when exact values matter more than proportional intuition.

Inputs

• mpactr object (filtered)
• data.table from qc_summary() output containing ion status (passed/failed filters)
• aggregated ion counts by filter status category

Outputs

• ggplot2 treemap object
• PNG file of rendered treemap visualization

How to apply

Extract the qc_summary() data.table, aggregate ion counts by filter status using data.table syntax, and calculate the percentage of total ions per status. Initialize a ggplot() call mapping status to fill aesthetic and ion count to the area parameter. Layer geom_treemap() to render rectangles sized by ion count, then geom_treemap_text() to overlay status labels and percentage annotations. Customize with scale_fill_brewer() (e.g., Greens palette) to distinguish status categories, suppress the legend, and apply ggplot2 theme() functions for publication formatting. Save the rendered plot to PNG.

Related tools

• ggplot2 (Core graphics framework for treemap layer specification and customization)
• treemapify (Provides geom_treemap() and geom_treemap_text() layers for rectangular treemap rendering)
• mpactr (Generates qc_summary() data.table containing ion filter status used as input) — https://github.com/mums2/mpactr
• data.table (Efficient aggregation and percentage calculation from qc_summary() output)
• scale_fill_brewer() (Applies categorical color palette (e.g., Greens) to distinguish filter status)

Examples

qc_dt <- qc_summary(filtered_mpactr_obj)[, .(ion_count = .N, pct = 100*.N/nrow(qc_summary(filtered_mpactr_obj))), by=status]; ggplot(qc_dt, aes(area=ion_count, fill=status, label=paste0(status, '\n', ion_count, ' (', round(pct,1), '%)'))) + geom_treemap() + geom_treemap_text(place='centre') + scale_fill_brewer(palette='Greens') + theme(legend.position='none') + ggsave('ion_filter_treemap.png')

Evaluation signals

• Treemap renders with exactly one rectangle per filter status category, sized proportional to ion count.
• geom_treemap_text() labels are legible and correctly display status name, ion count, and percentage (sum to 100%).
• Color palette is applied consistently and legend is suppressed when specified.
• PNG file is written to disk with expected dimensions and no rendering artifacts.
• Ion counts in treemap match aggregated values from qc_summary() data.table (no data loss or duplication).

Limitations

• Treemap readability degrades with more than ~6–8 status categories; extremely granular status hierarchies may require faceting or hierarchical treemaps.
• Text labels may overlap or become unreadable if rectangles are too small; aggregate data or increase figure dimensions as needed.
• Treemapify's geom_treemap() does not natively support interactive tooltips; use plotly::ggplotly() for interactivity or plotly treemaps for hover annotations.
• Color blindness accessibility depends on palette choice; scale_fill_brewer() Greens is red–green colorblind-safe, but confirm with CVD simulators for other palettes.

Evidence

• [other] Ion counts and percentages by status are computed from qc_summary() output using data.table syntax, then rendered as a treemap with geom_treemap() and geom_treemap_text() to display status labels, ion counts, and percentages: "Ion counts and percentages by status are computed from qc_summary() output using data.table syntax, then rendered as a treemap with geom_treemap() and geom_treemap_text() to display status labels,"
• [other] Create a treemap using ggplot2 geom_treemap() and geom_treemap_text() with Greens palette, no legend, sized by ion count and labeled with status and percentage.: "Create a treemap using ggplot2 geom_treemap() and geom_treemap_text() with Greens palette, no legend, sized by ion count and labeled with status and percentage"
• [other] The visualization can be customized with ggplot2 scale_fill_brewer() and theme() functions.: "The visualization can be customized with ggplot2 scale_fill_brewer() and theme() functions"