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Klaften, M. ; Hrabě de Angelis, M.

ARTS: A web-based tool for the set-up of high-throughput genome-wide mapping panels for the SNP genotyping of mouse mutants.

Nucleic Acids Res. 33, 2, W496-W500 (2005)
Verlagsversion Volltext DOI PMC
Open Access Gold
Creative Commons Lizenzvertrag
Genome-wide mapping in the identification of novel candidate genes has always been the standard method in genetics and genomics to correlate a clinically interesting phenotypic trait with a genotype. However, the performance of a mapping experiment using classical microsatellite approaches can be very time consuming. The high-throughput analysis of single-nucleotide polymorphisms (SNPs) has the potential of being the successor of microsatellite analysis routinely used for these mapping approaches, where one of the major obstacles is the design of the appropriate SNP marker set itself. Here we report on ARTS, an advanced retrieval tool for SNPs, which allows researchers to comb freely the public mouse dbSNP database for multiple reference and test strains. Several filters can be applied in order to improve the sensitivity and the specificity of the search results. By employing the panel generator function of this program, it is possible to abbreviate the extraction of reliable sequence data for a large marker panel including several different mouse strains from days to minutes. The concept of ARTS is easily adaptable to other species for which SNP databases are available, making it a versatile tool for the use of SNPs as markers for genotyping. The web interface is accessible at http://andromeda.gsf.de/arts.
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Publikationstyp Artikel: Journalartikel
Dokumenttyp Wissenschaftlicher Artikel
Korrespondenzautor
Schlagwörter MUTAGENESIS
ISSN (print) / ISBN 0305-1048
e-ISSN 1362-4962
Zeitschrift Nucleic Acids Research
Quellenangaben Band: 33, Heft: SUPPL. 2, Seiten: W496-W500, Artikelnummer: , Supplement: 2
Verlag Oxford University Press
Nichtpatentliteratur Publikationen
Begutachtungsstatus Peer reviewed
Institut(e) Institute of Experimental Genetics (IEG)