{"title":"SEA v2.0:用于数量性状混合主基因加多基因遗传分析的R软件包","authors":"Jing-Tian Wang, Ya-Wen Zhang, Yingying Du, Wen-Long Ren, Hong-Fu Li, Wenying Sun, Chao Ge, Yuan-Ming Zhang","doi":"10.3724/sp.j.1006.2022.14088","DOIUrl":null,"url":null,"abstract":": The phenotypic values for quantitative trait from bi-parental segregation populations can be used to identify its mixed major genes plus polygenes inheritance model, which provides important information for the genetic basis of quantitative traits and crop breeding. To comprehensively summarize the research results of methodological advances, add the new functions of the software and correct its shortcomings in previous versions, an R software package SEA v2.0 with interactive graphical user inter-face is developed under R studio–1.4.1103 platform and R environment. In this software, there were 14 types of bi-parental segregation populations, and each type included four modules: data input, data analysis, posterior probability calculation, and distribution curve drawing. To save running time, doParallel was used to conduct parallel computing, data.table was used to quickly read and write datasets, and MASS was used to estimate the parameters in component distributions. KScorrect, kolmim, and shiny packages were used to simplify the programs. As long as users uploaded the data file with *.csv format and set the related parameters, the results could be quickly displayed. The software was validated by real data analysis of soybean podding habit and Monte Carlo simulation studies, and can be downloaded from https://cran.r-project.org/web/packages/SEA/index.html.","PeriodicalId":52132,"journal":{"name":"作物学报","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"SEA v2.0: an R software package for mixed major genes plus polygenes inheritance analysis of quantitative traits\",\"authors\":\"Jing-Tian Wang, Ya-Wen Zhang, Yingying Du, Wen-Long Ren, Hong-Fu Li, Wenying Sun, Chao Ge, Yuan-Ming Zhang\",\"doi\":\"10.3724/sp.j.1006.2022.14088\",\"DOIUrl\":null,\"url\":null,\"abstract\":\": The phenotypic values for quantitative trait from bi-parental segregation populations can be used to identify its mixed major genes plus polygenes inheritance model, which provides important information for the genetic basis of quantitative traits and crop breeding. To comprehensively summarize the research results of methodological advances, add the new functions of the software and correct its shortcomings in previous versions, an R software package SEA v2.0 with interactive graphical user inter-face is developed under R studio–1.4.1103 platform and R environment. In this software, there were 14 types of bi-parental segregation populations, and each type included four modules: data input, data analysis, posterior probability calculation, and distribution curve drawing. To save running time, doParallel was used to conduct parallel computing, data.table was used to quickly read and write datasets, and MASS was used to estimate the parameters in component distributions. KScorrect, kolmim, and shiny packages were used to simplify the programs. As long as users uploaded the data file with *.csv format and set the related parameters, the results could be quickly displayed. The software was validated by real data analysis of soybean podding habit and Monte Carlo simulation studies, and can be downloaded from https://cran.r-project.org/web/packages/SEA/index.html.\",\"PeriodicalId\":52132,\"journal\":{\"name\":\"作物学报\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"作物学报\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3724/sp.j.1006.2022.14088\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"作物学报","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3724/sp.j.1006.2022.14088","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
SEA v2.0: an R software package for mixed major genes plus polygenes inheritance analysis of quantitative traits
: The phenotypic values for quantitative trait from bi-parental segregation populations can be used to identify its mixed major genes plus polygenes inheritance model, which provides important information for the genetic basis of quantitative traits and crop breeding. To comprehensively summarize the research results of methodological advances, add the new functions of the software and correct its shortcomings in previous versions, an R software package SEA v2.0 with interactive graphical user inter-face is developed under R studio–1.4.1103 platform and R environment. In this software, there were 14 types of bi-parental segregation populations, and each type included four modules: data input, data analysis, posterior probability calculation, and distribution curve drawing. To save running time, doParallel was used to conduct parallel computing, data.table was used to quickly read and write datasets, and MASS was used to estimate the parameters in component distributions. KScorrect, kolmim, and shiny packages were used to simplify the programs. As long as users uploaded the data file with *.csv format and set the related parameters, the results could be quickly displayed. The software was validated by real data analysis of soybean podding habit and Monte Carlo simulation studies, and can be downloaded from https://cran.r-project.org/web/packages/SEA/index.html.
作物学报Agricultural and Biological Sciences-Agronomy and Crop Science
CiteScore
1.70
自引率
0.00%
发文量
89
期刊介绍:
The major aims of AAS are to report the progresses in the disciplines of crop breeding, crop genetics, crop cultivation, crop physiology, ecology, biochemistry, germplasm resources, grain chemistry, grain storage and processing, bio-technology and biomathematics etc. mainly in China and abroad. AAS provides regular columns for Original papers, Reviews, and Research notes. The strict peer-review procedure guarantees the academic level and raises the reputation of the journal. The readership of AAS is for crop science researchers, students of agricultural colleges and universities, and persons with similar academic level.