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MAPtools:用于测序定位、QTL测序分析与可视化的命令行工具。

MAPtools: command-line tools for mapping-by-sequencing and QTL-Seq analysis and visualization.

作者信息

Martínez-Guardiola César, Parreño Ricardo, Candela Héctor

机构信息

Instituto de Bioingeniería, Universidad Miguel Hernández de Elche, Campus de Elche, Elche, 03202, Spain.

出版信息

Plant Methods. 2024 Jul 17;20(1):107. doi: 10.1186/s13007-024-01222-2.

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 .

摘要

背景

经典诱变是一种强大的工具,使研究人员能够阐明许多模式物种中大量过程的分子和遗传基础。这些方法与现代大规模平行测序技术的整合,最初是在模式物种中,目前也在许多作物物种中,正在加速对一系列具有农学意义的性状潜在基因的鉴定。

结果

我们开发了MAPtools,这是一个开源的Python3应用程序,专门设计用于分析来自混合分离群体分析实验的基因组数据,包括测序定位(MBS)和数量性状位点测序(QTL-seq)实验。我们使用近期文献中发表的数据集对MAPtools进行了广泛测试。

结论

MAPtools为用户提供了灵活性,可通过各种命令定制其生物信息学流程,这些命令用于计算基于等位基因计数的统计数据、生成图表以精确定位候选区域,以及注释单核苷酸多态性(SNP)和插入缺失(indel)突变的影响。虽然该程序已在植物中进行了广泛测试,但它具有通用性,适用于任何能够生成定位群体且有测序基因组的物种。

可用性和实现方式

MAPtools根据GPL v3.0许可提供,并作为一个Python3包在https://github.com/hcandela/MAPtools上记录。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/01b9/11253474/cae4a2fd2e8d/13007_2024_1222_Fig1_HTML.jpg

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