Function Index & S3 Class System Breakdown

qtl2ggplot organizes its source functions across 24 R source files and C++ routines in R/ and src/. Functions are grouped into five core functional categories:

1. S3 Autoplot Methods & Dispatch

qtl2ggplot integrates with ggplot2::autoplot() to provide unified plotting interfaces for qtl2 data structures:

Method	S3 Target Class	Source File	Description
`autoplot.scan1()`	`scan1`	`R/ggplot_scan1.R`	Dispatch method for genome-wide LOD score profile curves
`autoplot.scan1coef()`	`scan1coef`	`R/ggplot_coef.R`	Dispatch method for founder allele effect curves along chromosomes
`autoplot.listof_scan1coef()`	`listof_scan1coef`	`R/ggplot_listof_scan1coef.R`	Dispatch method for multi-model or multi-region coefficient comparisons
`autoplot.genes()`	`genes`	`R/ggplot_genes.R`	Dispatch method for gene exon track visualization

2. Specialized Plot Generators & Multi-Panel Layouts

Function	Primary Role	Source File
`ggplot_scan1()`	Plots LOD score profiles across single or multiple phenotypes	`R/ggplot_scan1.R`
`ggplot_coef()` / `ggplot_coefCC()`	Plots QTL effect curves, founder allele estimates, and BLUPs	`R/ggplot_coef.R`
`ggplot_coef_and_lod()`	Combines coefficient curves and LOD scores into a dual-panel figure	`R/ggplot_coef_and_lod.R`
`ggplot_snpasso()`	Manhattan-style plot of high-density SNP association results	`R/ggplot_snpasso.R`
`ggplot_genes()`	Renders gene locus structures and exon/intron tracks	`R/ggplot_genes.R`
`ggplot_snpasso_and_genes()`	Aligns SNP association peaks directly above gene locus maps	`R/ggplot_snpasso_and_genes.R`
`ggplot_pxg()` / `mean_pxg()`	Phenotype-by-genotype scatter plots and cell mean summaries	`R/ggplot_pxg.R`
`ggplot_onegeno()`	Visualizes chromosome genotype probabilities for a single subject	`R/ggplot_onegeno.R`
`ggplot_peaks()`	Overview plot summarizing LOD peak locations across chromosomes	`R/ggplot_peaks.R`

3. Summary & Object Manipulation Methods

Function / Method	S3 Class	Description
`summary.scan1()` / `summary_scan1()`	`scan1`	Extracts peak LOD locations, positions, and chromosome tags
`summary.scan1coef()` / `summary_scan1coef()`	`scan1coef`	Summarizes maximum allele effect positions and contrast estimates
`summary.listof_scan1coef()`	`listof_scan1coef`	Summarizes peak locations across list of coefficient objects
`subset.listof_scan1coef()` / `[.listof_scan1coef`	`listof_scan1coef`	Subsets list-of-scan1coef objects by chromosome or model index

4. Map Alignment & SNP Utility Helpers

align_scan1_map(): Aligns physical (Mbp) or genetic (cM) maps with scan1 LOD matrices (R/align_scan1_map.R).
color_patterns(): Manages color palettes for strain patterns and allele contrasts (R/color_patterns.R).
sdp_to_pattern(): Converts Strain Distribution Patterns (SDP) into strain pattern strings (R/sdp_to_pattern.R).
snpinfo_to_map() / snpinfo_to_haplos(): Extracts genetic maps and haplotype structures from SNP info objects (R/snpinfo_to_map.R).

5. High-Performance C++ Extensions

arrange_genes(): C++ function compiled via Rcpp (src/arrange_genes.cpp) that computes vertical layout rows for gene locus tracks, ensuring gene names and exon blocks never overlap visually.