Type 2 diabetes GWAS
Association peaks across a type 2 diabetes GWAS.
Manhattan Plot Generator
FigranTurn GWAS summary statistics into a Manhattan plot and QQ plot in your browser.
- PLINK, REGENIE, SAIGE
- Millions of variants
- Free SVG and PNG
Processing
Drop a summary statistics file here
Manhattan plot examples
Explore association patterns across traits and species.
Height GWAS
Dense association signals for adult height.
LDL cholesterol
Lipid associations across the genome.
Rheumatoid arthritis
A prominent association in the HLA region.
Asthma: Manhattan + QQ
A Manhattan plot alongside its QQ plot.
Plant GWAS, five chromosomes
Five plant chromosomes with a Bonferroni threshold.
How to make a Manhattan plot
Import summary statistics and choose the display settings for your figure.
1Import data
Import a GWAS summary statistics file or paste a small table.
2Check columns
Confirm chromosome, position, P value and optional variant ID columns.
3Choose thresholds and labels
Set the significance thresholds, locus window and labels.
4Export your figure
Download a PNG or SVG, or export the loci table.
GWAS summary statistics formats
Common PLINK, REGENIE, SAIGE, BOLT-LMM, GEMMA, GAPIT, GWAS-SSF and METAL columns are recognized. Verify the mapping before plotting.
| Format | Chromosome | Position | P value | Variant ID |
|---|---|---|---|---|
| PLINK 1.9 | CHR | BP | P | SNP |
| PLINK 2 | CHROM | POS | P / LOG10_P | ID |
| REGENIE | CHROM | GENPOS | LOG10P | ID |
| SAIGE | CHR | POS | p.value | MarkerID |
| BOLT-LMM | CHR | BP | P_BOLT_LMM | SNP |
| GEMMA | chr | ps | p_wald | rs |
| GAPIT / TASSEL | Chromosome | Position | P.value | SNP |
| GWAS-SSF | chromosome | base_pair_location | p_value / neg_log_10_p_value | rsid / variant_id |
| PheWeb / FinnGen | chrom | pos | pval / mlogp | rsids |
| METAL | — | — | P-value | MarkerName |
| MAGMA / EWAS | CHR | START / MAPINFO | P | GENE / CpG |
References: REGENIE documentation · GWAS-SSF specification
Reading a Manhattan plot
Each point represents a variant. Chromosomes run along the horizontal axis and stronger associations appear higher on the vertical axis. Peaks can contain many correlated variants.
- 1Chromosomes run from left to right.
- 2Points above the line pass the significance threshold.
- 3A peak groups nearby associated variants.
- 4The lead variant has the smallest P value within its window.
Genome-wide significance thresholds
The conventional human GWAS threshold is 5 × 10⁻⁸; 1 × 10⁻⁵ is a suggestive threshold. Bonferroni uses 0.05 divided by the number of plotted variants.
| Genome-wide | 5 × 10⁻⁸ |
|---|---|
| Suggestive | 1 × 10⁻⁵ |
| Bonferroni | 0.05 / m |
References: Pe’er et al. 2008 · Turner 2018
QQ plot and genomic inflation (λGC)
A GWAS QQ plot compares observed P values with their expected distribution. The genomic inflation factor is the median observed χ² statistic divided by its null median; population structure and polygenicity can both increase it.
References: Devlin & Roeder 1999 · Bulik-Sullivan et al. 2015
Manhattan plot FAQ
What is a Manhattan plot?
A Manhattan plot shows each variant by genomic position and −log10 P value. Peaks identify regions associated with a trait.
How do I make a Manhattan plot in R?
Use qqman::manhattan(gwasResults, chr = "CHR", bp = "BP", p = "P", snp = "SNP"). This tool uses similar columns without requiring code.
Can it handle a full GWAS file with millions of variants?
Yes. Files are read in your browser without upload, up to 30 million rows. Overlapping background points are thinned; significant points are retained.
Why is 5 × 10⁻⁸ the genome-wide significance threshold?
It approximates a Bonferroni correction for one million independent tests. Other species and study designs may need a different threshold.
What does λGC mean, and is 1.1 too high?
λGC compares the median observed χ² statistic with its null expectation. There is no universal cutoff: polygenicity and large samples can raise it as well as population structure.
How are lead SNPs and loci defined here?
A lead is the most significant variant in a distance window, 500 kb on each side by default. This is not LD clumping and does not use a reference panel.
Can I label a SNP with its nearest gene?
Yes. Select a human genome version and nearest-gene labels. For example, rs7903146 is at chr10:114758349 in GRCh37 and chr10:112998590 in GRCh38. The closest protein-coding gene is a positional annotation, not proof of a causal gene.
Can this make a Miami plot or regional association plot?
No. This tool makes Manhattan and QQ plots; it does not make Miami plots or LD-colored regional association plots such as LocusZoom.
Make your Manhattan plot
Turn your summary statistics into a figure and locus table.
Make your Manhattan plot