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https://hdl.handle.net/11000/35313
MAPtools: command-line tools for mappingby-sequencing and QTL-Seq analysis and visualization
Título : MAPtools: command-line tools for mappingby-sequencing and QTL-Seq analysis and visualization |
Autor : Martínez-Guardiola, César Parreño-Montoro, Ricardo Candela, Héctor |
Editor : BioMed Central |
Departamento: Departamentos de la UMH::Biología Aplicada |
Fecha de publicación: 2024-07-17 |
URI : https://hdl.handle.net/11000/35313 |
Resumen :
Abstract
Background Classical mutagenesis is a powerful tool that has allowed researchers to elucidate the molecular and
genetic basis of a plethora of processes in many model species. The integration of these methods with modern
massively parallel sequencing techniques, initially in model species but currently also in many crop species, is
accelerating the identification of genes underlying a wide range of traits of agronomic interest.
Results We have developed MAPtools, an open-source Python3 application designed specifically for the analysis of
genomic data from bulked segregant analysis experiments, including mapping-by-sequencing (MBS) and quantitative
trait locus sequencing (QTL-seq) experiments. We have extensively tested MAPtools using datasets published in
recent literature.
Conclusions MAPtools gives users the flexibility to customize their bioinformatics pipeline with various commands
for calculating allele count-based statistics, generating plots to pinpoint candidate regions, and annotating the effects
of SNP and indel mutations. While extensively tested with plants, the program is versatile and applicable to any
species for which a mapping population can be generated and a sequenced genome is available.
Availability and implementation MAPtools is available under GPL v3.0 license and documented as a Python3
package at https://github.com/hcandela/MAPtools.
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Área de conocimiento : CDU: Ciencias puras y naturales: Biología |
Tipo de documento : info:eu-repo/semantics/article |
Derechos de acceso: info:eu-repo/semantics/openAccess Attribution-NonCommercial-NoDerivatives 4.0 Internacional |
DOI : https://doi.org/10.1186/s13007-024-01222-2 |
Aparece en las colecciones: Artículos Biología Aplicada
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La licencia se describe como: Atribución-NonComercial-NoDerivada 4.0 Internacional.