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  Fur: Find unique genomic regions for diagnostic PCR

Haubold, B., Klötzl, F., Hellberg, L., Thompson, D., & Cavalar, M. (2021). Fur: Find unique genomic regions for diagnostic PCR. Bioinformatics, 37(15), 2081-2087. doi:10.1093/bioinformatics/btab059.

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 Urheber:
Haubold, Bernhard1, Autor           
Klötzl, Fabian1, Autor           
Hellberg, Lars, Autor
Thompson, Daniel, Autor
Cavalar, Markus, Autor
Affiliations:
1Research Group Bioinformatics, Department Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society, ou_1445644              

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 Zusammenfassung: Unique marker sequences are highly sought after in molecular diagnostics. Nevertheless, there are only few programs available to search for marker sequences, compared to the many programs for similarity search. We therefore wrote the program Fur for Finding Unique genomic Regions.Fur takes as input a sample of target sequences and a sample of closely related neighbors. It returns the regions present in all targets and absent from all neighbors. The recently published program genmap can also be used for this purpose and we compared it to fur. When analyzing a sample of 33 genomes representing the major phylogroups of E.coli, fur was 40 times faster than genmap but used three times more memory. On the other hand, genmap yielded three times more markers, but they were less accurate when tested in silico on a sample of 237 E.coli genomes. We also designed phylogroup-specific PCR primers based on the markers proposed by genmap and fur, and tested them by analyzing their virtual amplicons in GenBank. Finally, we used fur to design primers specific to a Lactobacillus species, and found excellent sensitivity and specificity in vitro.Fur sources and documentation are available from https://github.com/evolbioinf/fur. The compiled software is posted as a docker container at https://hub.docker.com/r/haubold/fox.Supplementary data are available at Bioinformatics online.

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Sprache(n): eng - English
 Datum: 2020-12-042020-09-092021-01-262021-01-302021-08
 Publikationsstatus: Erschienen
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 Identifikatoren: DOI: 10.1093/bioinformatics/btab059
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Titel: Bioinformatics
Genre der Quelle: Zeitschrift
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Ort, Verlag, Ausgabe: Oxford : Oxford University Press
Seiten: - Band / Heft: 37 (15) Artikelnummer: - Start- / Endseite: 2081 - 2087 Identifikator: ISSN: 1367-4803
CoNE: https://pure.mpg.de/cone/journals/resource/954926969991