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MAPtools: command-line tools for mappingby-sequencing and QTL-Seq analysis and visualization


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Title:
MAPtools: command-line tools for mappingby-sequencing and QTL-Seq analysis and visualization
Authors:
Martínez-Guardiola, César  
Parreño-Montoro, Ricardo  
Candela, Héctor
Editor:
BioMed Central
Department:
Departamentos de la UMH::Biología Aplicada
Issue Date:
2024-07-17
URI:
https://hdl.handle.net/11000/35313
Abstract:
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.
Knowledge area:
CDU: Ciencias puras y naturales: Biología
Type of document:
info:eu-repo/semantics/article
Access rights:
info:eu-repo/semantics/openAccess
Attribution-NonCommercial-NoDerivatives 4.0 Internacional
DOI:
https://doi.org/10.1186/s13007-024-01222-2
Appears in Collections:
Artículos Biología Aplicada



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