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Researchers studying the genomic basis of complex diseases or traits frequently need to select optimal sets of Single Nucleotide Polymorphisms (SNPs) from the millions described in databases. This is a difficult computational problem, since many different criteria have to be considered simultaneously. SYSNPs is the first web server implementing algorithms that allow for efficient and simultaneous consideration of all the relevant criteria in order to obtain optimal sets of SNPs for arbitrarily large sets of genes, genomic regions or Gene Ontology (GO) terms. Also, users can easily consider functional properties, technological information and tagging information from their choice populations. SYSNPs optimizes SNP selection thus reducing genotyping costs. For example, the time needed to select appropriate tag-SNPs to study a set of 100 genes is reduced from days to a few minutes. In addition, the task is simplified from a partially automated search in several databases by means of several different tools to the easy use of a simple browser.


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Whole genome scans analyze large sets of genetic markers, mainly single nucleotide polymorphisms, over the entire genome in order to find variants and regions associated with complex traits so these can be further investigated. Analyzing the results of such scans becomes difficult due to multiple testing problems and to the genomic distributions of recombination, linkage disequilibrium and true associations, which generate an extremely complex network of dependences between markers. Here we present Association Cluster Detector (ACD), a simple tool aiming to ease the analysis of the results of whole genome scans. ACD facilitates correction for multiple tests using several standard procedures and implements a sliding-window heuristic method that helps in detecting potentially interesting candidate regions by exploiting the property of non-random distribution of significantly associated markers.~T

Marques-Bonet T., Oscar Lao, Robert Goertsches, Manuel Comabella, Xavier Montalban, Arcadi Navarro. Association Cluster Detector: a tool for heuristic detection of association clusters in whole-genome scans.

Bioinformatics 2005 , 21 (s2):180-181.



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