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RAD-R scripts: R pipeline for RAD-seq from FASTQ files to linkage maps construction and run R/QTL, operating only at copying and pasting scripts into R console

Coupled with the reduction in sequencing costs, the number of RAD-seq analysis have been surging, generating vast genetic knowledge in relation with many crops. Specialized platforms might be intimidating to non-expert users and difficult to implement on each computer despite the growing interest in...

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Detalles Bibliográficos
Autor principal: Seki, Kousuke
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Japanese Society of Breeding 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8661492/
https://www.ncbi.nlm.nih.gov/pubmed/34912169
http://dx.doi.org/10.1270/jsbbs.20159
Descripción
Sumario:Coupled with the reduction in sequencing costs, the number of RAD-seq analysis have been surging, generating vast genetic knowledge in relation with many crops. Specialized platforms might be intimidating to non-expert users and difficult to implement on each computer despite the growing interest in the usage of the dataset obtained by high-throughput sequencing. Therefore, RAD-R scripts were developed on Windows10 for RAD-seq analysis, allowing users who are not familiar with bioinformatics to easily analyze big sequence data. These RAD-R scripts that run a flow from raw sequence reads of F(2) population for the self-fertilization plants to the linkage map construction as well as the QTL analysis can be also useful to many users with limited experience due to the simplicity of copying Excel cells into the R console. During the comparison of linkage maps constructed by RAD-R scripts and Stacks, RAD-R scripts were shown to construct the linkage map with less missing genotype data and a shorter total genetic distance. QTL analysis results can be easily obtained by selecting the reliable genotype data that is visually inferred to be appropriate for error correction from the genotype data files created by RAD-R scripts.