# Manhattan plot

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{{short description|Method to display data used in genetic analysis}}
thumb|300px|An illustration of a Manhattan plot depicting several strongly associated risk loci
A '''Manhattan plot''' is a type of [plot](/source/Plot_(graphics)), usually used to display data with a large number of data-points, many of non-zero amplitude, and with a distribution of higher-magnitude values. The plot is commonly used in [genome-wide association studies](/source/Genome-wide_association_study) (GWAS) to display significant [SNPs](/source/Single-nucleotide_polymorphism).<ref name=East>{{cite journal|pmid=20581876|doi=10.1038/ng0710-558|year=2010|last1=Gibson|first1=Greg|title=Hints of hidden heritability in GWAS |volume=42|pages=558–560|journal=Nature Genetics|issue=7|s2cid=34546516 }}</ref>

It gains its name from the similarity of such a plot to the [Manhattan](/source/Manhattan) [skyline](/source/skyline): a profile of [skyscrapers](/source/skyscrapers) towering above the lower level "buildings" which vary around a lower height.

==GWAS==
In GWAS Manhattan plots, genomic coordinates are displayed along the ''x''-axis, with the negative [logarithm](/source/logarithm) of the association [''p''-value](/source/p-value) for each [single nucleotide polymorphism](/source/single_nucleotide_polymorphism) (SNP) displayed on the ''y''-axis, meaning that each dot on the Manhattan plot signifies an SNP. Because the strongest associations have the smallest ''p''-values (e.g., 10<sup>−15</sup>), their negative logarithms will be the greatest (e.g., 15). The different colors of each block usually show the extent of each chromosome.

==References==
{{Reflist}}

{{Commons category|Manhattan plot}}

Category:Statistical charts and diagrams
Category:Genetic epidemiology
Category:Single-nucleotide polymorphisms

{{statistics-stub}}

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Adapted from the Wikipedia article [Manhattan plot](https://en.wikipedia.org/wiki/Manhattan_plot) by Wikipedia contributors ([contributor history](https://en.wikipedia.org/wiki/Manhattan_plot?action=history)). Available under [Creative Commons Attribution-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-sa/4.0/). Changes may have been made.
