ManhattanPlot

A Manhattan plot displays GWAS p-values across the genome. Each point represents a SNP; the x-axis spans chromosomes and the y-axis shows −log₁₀(p-value). Dashed threshold lines are drawn automatically at genome-wide and suggestive significance levels. Chromosomes are colored with an alternating two-color scheme.

When to Use

GWAS studies: Standard plot for genome-wide association results
Rare variant analysis: Display exome-wide or gene-based p-values
eQTL mapping: Show expression QTL associations
TWAS: Transcriptome-wide association studies
Meta-analysis: Combined GWAS results across cohorts
Quality control: Identify systematic bias or inflation

Basic Example

use kuva::plot::{ManhattanPlot, GenomeBuild};
use kuva::backend::svg::SvgBackend;
use kuva::render::render::render_multiple;
use kuva::render::layout::Layout;
use kuva::render::plots::Plot;

// (chrom, bp_position, pvalue) from PLINK/GCTA
let data: Vec<(String, f64, f64)> = vec![
    ("1".into(), 100_000_000.0, 3e-10),
    ("6".into(), 50_000_000.0, 8e-9),
    // ... thousands more SNPs
];

let mp = ManhattanPlot::new()
    .with_data_bp(data, GenomeBuild::Hg38)
    .with_label_top(10)
    .with_legend("GWAS thresholds");

let plots = vec![Plot::Manhattan(mp)];
let layout = Layout::auto_from_plots(&plots)
    .with_title("GWAS — Base-pair Coordinates (GRCh38)")
    .with_x_label("Chromosome")
    .with_y_label("−log₁₀(p-value)");

let svg = SvgBackend.render_scene(&render_multiple(plots, layout));
std::fs::write("manhattan.svg", svg).unwrap();

Input Modes

Three methods map (chrom, …, pvalue) onto the cumulative x-axis:

Mode 1: Sequential Index — `with_data`

SNPs placed at consecutive integer x positions within each chromosome.

let data: Vec<(String, f64)> = vec![
    ("1".into(), 0.42), ("1".into(), 3e-8),
    ("2".into(), 0.17), ("2".into(), 5e-6),
];
let mp = ManhattanPlot::new().with_data(data);

Use when base-pair positions are unavailable.

Mode 2: Base-pair Coordinates — `with_data_bp`

SNP x = chromosome cumulative offset + bp position. Standard mode for GWAS.

let data = vec![
    ("1", 100_000_000_f64, 3e-10_f64),
    ("6",  50_000_000_f64, 8e-9),
];
let mp = ManhattanPlot::new()
    .with_data_bp(data, GenomeBuild::Hg38);

All chromosomes in the build appear as labeled bands even if they contain no data.

GenomeBuild Options

GenomeBuild::Hg19 — GRCh37 / hg19 (24 chromosomes + MT)
GenomeBuild::Hg38 — GRCh38 / hg38 (24 chromosomes + MT)
GenomeBuild::T2T — T2T-CHM13 v2.0 / hs1 (telomere-to-telomere)
GenomeBuild::Custom(vec) — User-supplied Vec<(chrom_name, size_bp)>

let build = GenomeBuild::Custom(vec![
    ("chr1".to_string(), 120_000_000),
    ("chr2".to_string(),  95_000_000),
    ("chrX".to_string(),  55_000_000),
]);
let mp = ManhattanPlot::new()
    .with_data_bp(data, build);

Mode 3: Pre-computed x — `with_data_x`

Supply explicit cumulative x coordinates.

let data = vec![
    ("A",  10.0_f64, 0.42_f64),
    ("A",  20.0,     3e-8),
    ("B", 120.0,     0.17),
    ("B", 130.0,     5e-6),
];
let mp = ManhattanPlot::new().with_data_x(data);

Use for custom or non-human genomes.

Key Methods

Thresholds

`with_genome_wide(threshold: f64)`

Set genome-wide significance in −log₁₀ scale (default 7.301 = p = 5×10⁻⁸).

let mp = ManhattanPlot::new()
    .with_genome_wide(8.0);  // p = 1e-8

Dashed red line drawn at this y position. Only points above this threshold are candidates for with_label_top labels.

`with_suggestive(threshold: f64)`

Set suggestive significance in −log₁₀ scale (default 5.0 = p = 1×10⁻⁵).

let mp = ManhattanPlot::new()
    .with_suggestive(4.0);  // p = 1e-4

Dashed gray line drawn at this y position.

Colors

`with_color_a(color: impl Into<String>)` / `with_color_b(color: impl Into<String>)`

Set colors for alternating chromosomes (default "steelblue" / "#5aadcb").

let mp = ManhattanPlot::new()
    .with_color_a("#1f77b4")
    .with_color_b("#aec7e8");

`with_palette(palette: Palette)`

Override two-color scheme with a full palette. Colors cycle across chromosomes.

use kuva::Palette;

let mp = ManhattanPlot::new()
    .with_palette(Palette::tol_bright());

Gene Labels

`with_label_top(n: usize)`

Label the n most significant points above the genome-wide threshold (lowest p-values).

let mp = ManhattanPlot::new()
    .with_label_top(10);  // label top 10 hits

`with_label_style(style: LabelStyle)`

Set label placement style (default LabelStyle::Nudge).

LabelStyle::Nudge (default) — Labels sorted by x and nudged vertically
LabelStyle::Exact — Labels at exact point position
LabelStyle::Arrow { offset_x, offset_y } — Labels offset with leader line

use kuva::plot::LabelStyle;

let mp = ManhattanPlot::new()
    .with_label_top(10)
    .with_label_style(LabelStyle::Arrow { offset_x: 10.0, offset_y: 14.0 });

`with_point_labels(iter)`

Attach specific gene/SNP labels to points by (chrom, x, label).

let mp = ManhattanPlot::new()
    .with_data_x(data)
    .with_point_labels(vec![
        ("1",  40.0, "BRCA2"),
        ("2", 140.0, "TP53"),
    ]);

The x value must match the coordinate assigned at data-load time.

Other Options

`with_point_size(size: f64)`

Set radius in pixels (default 2.5).

let mp = ManhattanPlot::new()
    .with_point_size(3.0);

`with_pvalue_floor(floor: f64)`

Set explicit p-value floor for −log10 transform. Points with pvalue == 0.0 clamped to this value.

let mp = ManhattanPlot::new()
    .with_pvalue_floor(1e-20);  // y-axis ceiling = 20

`with_legend(label: impl Into<String>)`

Enable legend showing genome-wide and suggestive threshold lines.

let mp = ManhattanPlot::new()
    .with_legend("GWAS thresholds");

Examples

Standard GWAS — GRCh38

let data: Vec<(String, f64, f64)> = vec![
    ("1".into(), 100_000_000.0, 3e-10),
    ("2".into(),  50_000_000.0, 1e-8),
    ("6".into(),  32_000_000.0, 5e-9),
    // ... thousands more SNPs
];

let mp = ManhattanPlot::new()
    .with_data_bp(data, GenomeBuild::Hg38)
    .with_genome_wide(7.301)   // 5e-8
    .with_suggestive(5.0)      // 1e-5
    .with_label_top(10)
    .with_legend("GWAS thresholds");

let plots = vec![Plot::Manhattan(mp)];
let layout = Layout::auto_from_plots(&plots)
    .with_title("Height GWAS — 100k samples")
    .with_x_label("Chromosome")
    .with_y_label("−log₁₀(p-value)");

Standard genome-wide thresholds with top 10 hits labeled.

Custom Genome Build

let build = GenomeBuild::Custom(vec![
    ("1".to_string(), 150_000_000),
    ("2".to_string(), 120_000_000),
    ("3".to_string(),  90_000_000),
]);

let data: Vec<(String, f64, f64)> = vec![
    ("1".into(), 80_000_000.0, 2e-8),
    ("2".into(), 50_000_000.0, 5e-7),
];

let mp = ManhattanPlot::new()
    .with_data_bp(data, build)
    .with_label_top(5);

let plots = vec![Plot::Manhattan(mp)];
let layout = Layout::auto_from_plots(&plots)
    .with_title("Custom Genome GWAS")
    .with_x_label("Chromosome")
    .with_y_label("−log₁₀(p-value)");

Non-human genome or custom chromosome set.

Custom Color Palette

use kuva::Palette;

let mp = ManhattanPlot::new()
    .with_data_bp(data, GenomeBuild::Hg38)
    .with_palette(Palette::tol_bright())
    .with_label_top(10);

let plots = vec![Plot::Manhattan(mp)];
let layout = Layout::auto_from_plots(&plots)
    .with_title("Custom Palette GWAS")
    .with_x_label("Chromosome")
    .with_y_label("−log₁₀(p-value)");

Colorblind-friendly Paul Tol palette.

Exome-wide Sequential Index

let data: Vec<(String, f64)> = vec![
    ("1".into(), 0.42), ("1".into(), 3e-8), ("1".into(), 5e-7),
    ("2".into(), 0.17), ("2".into(), 5e-6), ("2".into(), 8e-9),
    // ... gene-based p-values
];

let mp = ManhattanPlot::new()
    .with_data(data)
    .with_genome_wide(6.0)     // Bonferroni: 0.05 / 20000 genes
    .with_label_top(5);

let plots = vec![Plot::Manhattan(mp)];
let layout = Layout::auto_from_plots(&plots)
    .with_title("Exome-wide Gene-based Test")
    .with_x_label("Chromosome")
    .with_y_label("−log₁₀(p-value)");

No base-pair positions; sequential index mode.

Zero p-values

p-values of exactly 0.0 are clamped at the smallest non-zero p-value (or pvalue_floor) to prevent infinite y positions.

Chromosome Names

Chromosome names are accepted with or without the "chr" prefix. Internally normalized to standard order: 1–22, X, Y, MT, then lexicographic.

Overview

Basic Plots

Statistical Plots

Scientific Plots

Network & Flow

ManhattanPlot

When to Use

Basic Example

Input Modes

Mode 1: Sequential Index — `with_data`

Mode 2: Base-pair Coordinates — `with_data_bp`

GenomeBuild Options

Mode 3: Pre-computed x — `with_data_x`

Key Methods

Thresholds

`with_genome_wide(threshold: f64)`

`with_suggestive(threshold: f64)`

Colors

`with_color_a(color: impl Into<String>)` / `with_color_b(color: impl Into<String>)`

`with_palette(palette: Palette)`

Gene Labels

`with_label_top(n: usize)`

`with_label_style(style: LabelStyle)`

`with_point_labels(iter)`

Other Options

`with_point_size(size: f64)`

`with_pvalue_floor(floor: f64)`

`with_legend(label: impl Into<String>)`

Examples

Standard GWAS — GRCh38

Custom Genome Build

Custom Color Palette

Exome-wide Sequential Index

Zero p-values

Chromosome Names

See Also

Build docs developers (and LLMs) love

Overview

Basic Plots

Statistical Plots

Scientific Plots

Network & Flow

​When to Use

​Basic Example

​Input Modes

​Mode 1: Sequential Index — with_data

​Mode 2: Base-pair Coordinates — with_data_bp

​GenomeBuild Options

​Mode 3: Pre-computed x — with_data_x

​Key Methods

​Thresholds

​with_genome_wide(threshold: f64)

​with_suggestive(threshold: f64)

​Colors

​with_color_a(color: impl Into<String>) / with_color_b(color: impl Into<String>)

​with_palette(palette: Palette)

​Gene Labels

​with_label_top(n: usize)

​with_label_style(style: LabelStyle)

​with_point_labels(iter)

​Other Options

​with_point_size(size: f64)

​with_pvalue_floor(floor: f64)

​with_legend(label: impl Into<String>)

​Examples

​Standard GWAS — GRCh38

​Custom Genome Build

​Custom Color Palette

​Exome-wide Sequential Index

​Zero p-values

​Chromosome Names

​See Also

Build docs developers (and LLMs) love

When to Use

Basic Example

Input Modes

Mode 1: Sequential Index — `with_data`

Mode 2: Base-pair Coordinates — `with_data_bp`

GenomeBuild Options

Mode 3: Pre-computed x — `with_data_x`

Key Methods

Thresholds

`with_genome_wide(threshold: f64)`

`with_suggestive(threshold: f64)`

Colors

`with_color_a(color: impl Into<String>)` / `with_color_b(color: impl Into<String>)`

`with_palette(palette: Palette)`

Gene Labels

`with_label_top(n: usize)`

`with_label_style(style: LabelStyle)`

`with_point_labels(iter)`

Other Options

`with_point_size(size: f64)`

`with_pvalue_floor(floor: f64)`

`with_legend(label: impl Into<String>)`

Examples

Standard GWAS — GRCh38

Custom Genome Build

Custom Color Palette

Exome-wide Sequential Index

Zero p-values

Chromosome Names

See Also