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A Manhattan plot is a type of plot, 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 (GWAS) to display significant SNPs .
An illustration of a Manhattan plot depicting several strongly associated risk loci. Each dot represents a SNP , with the X-axis showing genomic location and Y-axis showing association level . This example is taken from a GWA study investigating kidney stone disease , so the peaks indicate genetic variants that are found more often in ...
The Manhattan plot is named as such as the statistically significant genes appear to show up as "skyscrapers" on the plot, and when there are many genes that are associated with the trait, the plot resembles the Manhattan skyline. Although the Manhattan plot image is for a GWAS study, TWAS results are shown the same way.
Over the years, the GWAS catalog has enhanced its data release frequency by adding features such as graphical user interface, ontology-supported search functionality and a curation interface. [ 3 ] The GWAS catalog is widely used to identify causal variants and understand disease mechanisms by biologists, bioinformaticians and other researchers.
In genome-wide association studies, genome-wide significance (abbreviated GWS) is a specific threshold for determining the statistical significance of a reported association between a given single-nucleotide polymorphism (SNP) and a given trait.
In bookkeeping, a bank reconciliation or Bank Reconciliation Statement (BRS) is the process by which the bank account balance in an entity’s books of account is reconciled to the balance reported by the financial institution in the most recent bank statement. Any difference between the two figures needs to be examined and, if appropriate ...
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Computational genomics refers to the use of computational and statistical analysis to decipher biology from genome sequences and related data, [1] including both DNA and RNA sequence as well as other "post-genomic" data (i.e., experimental data obtained with technologies that require the genome sequence, such as genomic DNA microarrays).