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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 | Rights: | Attribution 4.0 International | 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 | Rights: | Attribution 4.0 International |
Appears in Collections: | Staff Publications Elements |
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