Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0086761
Title: ArchiLD: Hierarchical visualization of linkage disequilibrium in human populations
Authors: Melchiotti R.
Rötzschke O.
Poidinger M. 
Keywords: ArchiLD data base
article
computer program
data base
gene control
gene expression
gene linkage disequilibrium
genetic conservation
genomics
genotype
human
single nucleotide polymorphism
Genetic Linkage
Genome, Human
Genotype
Humans
Linkage Disequilibrium
Polymorphism, Single Nucleotide
Software
Issue Date: 2014
Citation: Melchiotti R., Rötzschke O., Poidinger M. (2014). ArchiLD: Hierarchical visualization of linkage disequilibrium in human populations. PLoS ONE 9 (1) : e86761. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0086761
Abstract: Linkage disequilibrium (LD) is an essential metric for selecting single-nucleotide polymorphisms (SNPs) to use in genetic studies and identifying causal variants from significant tag SNPs. The explosion in the number of polymorphisms that can now be genotyped by commercial arrays makes the interpretation of triangular correlation plots, commonly used for visualizing LD, extremely difficult in particular when large genomics regions need to be considered or when SNPs in perfect LD are not adjacent but scattered across a genomic region. We developed ArchiLD, a user-friendly graphical application for the hierarchical visualization of LD in human populations. The software provides a powerful framework for analyzing LD patterns with a particular focus on blocks of SNPs in perfect linkage as defined by r2. Thanks to its integration with the UCSC Genome Browser, LD plots can be easily overlapped with additional data on regulation, conservation and expression. ArchiLD is an intuitive solution for the visualization of LD across large or highly polymorphic genomic regions. Its ease of use and its integration with the UCSC Genome Browser annotation potential facilitates the interpretation of association results and enables a more informed selection of tag SNPs for genetic studies. © 2014 Melchiotti et al.
Source Title: PLoS ONE
URI: https://scholarbank.nus.edu.sg/handle/10635/161435
ISSN: 1932-6203
DOI: 10.1371/journal.pone.0086761
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