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• W2161027665 abstract "Abstract Motivation: Current high-throughput sequencing technologies allow cost-efficient genotyping of millions of single nucleotide polymorphisms (SNPs) for hundreds of samples. However, the tools that are currently available for constructing linkage maps are not well suited for large datasets. Linkage maps of large datasets would be helpful in de novo genome assembly by facilitating comprehensive genome validation and refinement by enabling chimeric scaffold detection, as well as in family-based linkage and association studies, quantitative trait locus mapping, analysis of genome synteny and other complex genomic data analyses. Results: We describe a novel tool, called Lepidoptera-MAP (Lep-MAP), for constructing accurate linkage maps with ultradense genome-wide SNP data. Lep-MAP is fast and memory efficient and largely automated, requiring minimal user interaction. It uses simultaneously data on multiple outbred families and can increase linkage map accuracy by taking into account achiasmatic meiosis, a special feature of Lepidoptera and some other taxa with no recombination in one sex (no recombination in females in Lepidoptera). We demonstrate that Lep-MAP outperforms other methods on real and simulated data. We construct a genome-wide linkage map of the Glanville fritillary butterfly (Melitaea cinxia) with over 40 000 SNPs. The data were generated with a novel in-house SOLiD restriction site-associated DNA tag sequencing protocol, which is described in the online supplementary material. Availability and implementation: Java source code under GNU general public license with the compiled classes and the datasets are available from http://sourceforge.net/users/lep-map. Contact: pasi.rastas@helsinki.fi Supplementary information: Supplementary data are available at Bioinformatics online." @default.
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• W2161027665 date "2013-09-26" @default.
• W2161027665 modified "2023-10-06" @default.
• W2161027665 title "Lep-MAP: fast and accurate linkage map construction for large SNP datasets" @default.
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• W2161027665 doi "https://doi.org/10.1093/bioinformatics/btt563" @default.
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