| 摘要: |
| 子代测定是动植物育种中的关键环节，一般使用混合线性模型基于限制性最大似然 (restricted maximum likehood, REML) 法来估算子代测定数据中随机效应的方差分量，并估计固定效应 ( 最佳线性无偏估计，BLUEs) 和预测随机效应 ( 最佳线性无偏预测，BLUPs)。当前动植物遗传评估的先锋软件是 ASReml，但其是商业软件，费用昂贵。虽然有如 Echidna 或 R 程序包 sommer 等免费软件，但是Echidna 软件用法复杂，而 R 程序包功能有限。因此本研究利用 R 语言基于 Echidna 软件编写 R 程序包AFEchidna，方便用户通过该程序包使用混合线性模型不仅可求解方差分量、遗传参数和随机效应 BLUP值，还可进行多个性状、多个方差结构和多个遗传参数的批量分析，不同模型间的比较以及基因组 BLUP分析。开发 AFEchidna 包来壮大遗传评估免费软件，并期望其效率能接近于商业软件。 |
| 关键词: REML 方差分量 遗传参数 批量分析 |
| DOI： |
| 分类号: |
| 基金项目:广东省重点领域研发计划项目林业专项 (2020B020215002) |
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| AFEchidna is A R Package for Genetic Evaluation of Plant and Animal Breeding Datasets |
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xiaolina1, weiruiyan2, tangzhiyin2, Zhangweihua3, linyuanzhen2
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1.Guangdong Provincial Key Laboratory of Silviculture, Protection and Utilization/Guangdong Academy of Forestry;2.South China Agricultural University;3.Guangdong Academy of Forestry
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| Abstract: |
| Progeny tests play important roles in plant and animal breeding programs, and mixed linear models are usually performed to estimate variance components of random effects, estimate the fixed effects (Best Linear Unbiased Estimates, BLUEs) and predict the random effects (Best Linear Unbiased Predictions, BLUPs) via restricted maximum likehood (REML) methods in progeny test datasets. The current pioneer software for genetic assessment is ASReml, but it is commercial and expensive. Although there is free software such as Echidna or the R package sommer, the Echidna syntax is complex and the R package functionality is limited. Therefore, this study aims to develop a R package named AFEchidna based on Echidna software. The mixed linear models are conveniently implemented for users through the AFEchidna package to solve variance components, genetic parameters and the BLUP values of random effects, and the batch analysis of multiple traits, multiple variance structures and multiple genetic parameters can be also performed, as well as comparison between different models and genomic BLUP analysis. The AFEchidna package is developed to expand free genetic assessment software with the expectation that its efficiency could be close to the commercial software. |
| Key words: REML variance components genetic parameters batch analysis |
