{"title":"利用 Bioconductor 的 HIBAG 软件包和 R 编程,开发用于利用 SNP 数据预测 HLA 等位基因的样本制备和模型创建的集成网络应用程序(Snips2HLA-HsG)","authors":"Balamurugan Sivaprakasam, Prasanna Sadagopan","doi":"10.21926/obm.genet.2402243","DOIUrl":null,"url":null,"abstract":"The present study introduces Snips2HLA-HsG, an integrated application designed for SNP genotype analysis and HLA allele type prediction. Leveraging attribute bagging, a powerful ensemble classifier technique from the Bioconductor HIBAG package, Snips2HLA-HsG offers a comprehensive response for genetic analysis. Accessible via https://snips2hla.shinyapps.io/hla_home/, the application distinguishes itself by prioritizing user-friendliness and integrating all-purpose functionalities, including sample preparation, model generation, HLA prediction, and accuracy assessment. In contrast to the fragmented landscape of existing HLA imputation software, this study addresses the need for an integrated, user-centric platform. By streamlining processes and enhancing accessibility, Snips2HLA-HsG ensures usability, even for biologists with limited computer proficiency. Future updates will address the choice between one or ten classifiers, aiming to optimize server utility and meet research needs effectively by adding more classifiers to utilize multiple cores for faster calculations. Looking ahead, Snips2HLA-HsG will undergo regular updates and maintenance to ensure continued effectiveness and relevance in genetic research. Maintenance efforts will focus on resolving issues or bugs and providing ongoing user support.","PeriodicalId":503721,"journal":{"name":"OBM Genetics","volume":"5 5","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-06-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Integrated Web Application (Snips2HLA-HsG) Development for Sample Preparation and Model Creation for HLA Allele Prediction with the SNP Data Using HIBAG Package of Bioconductor and R Programming\",\"authors\":\"Balamurugan Sivaprakasam, Prasanna Sadagopan\",\"doi\":\"10.21926/obm.genet.2402243\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The present study introduces Snips2HLA-HsG, an integrated application designed for SNP genotype analysis and HLA allele type prediction. Leveraging attribute bagging, a powerful ensemble classifier technique from the Bioconductor HIBAG package, Snips2HLA-HsG offers a comprehensive response for genetic analysis. Accessible via https://snips2hla.shinyapps.io/hla_home/, the application distinguishes itself by prioritizing user-friendliness and integrating all-purpose functionalities, including sample preparation, model generation, HLA prediction, and accuracy assessment. In contrast to the fragmented landscape of existing HLA imputation software, this study addresses the need for an integrated, user-centric platform. By streamlining processes and enhancing accessibility, Snips2HLA-HsG ensures usability, even for biologists with limited computer proficiency. Future updates will address the choice between one or ten classifiers, aiming to optimize server utility and meet research needs effectively by adding more classifiers to utilize multiple cores for faster calculations. Looking ahead, Snips2HLA-HsG will undergo regular updates and maintenance to ensure continued effectiveness and relevance in genetic research. Maintenance efforts will focus on resolving issues or bugs and providing ongoing user support.\",\"PeriodicalId\":503721,\"journal\":{\"name\":\"OBM Genetics\",\"volume\":\"5 5\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-06-14\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"OBM Genetics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.21926/obm.genet.2402243\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"OBM Genetics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21926/obm.genet.2402243","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Integrated Web Application (Snips2HLA-HsG) Development for Sample Preparation and Model Creation for HLA Allele Prediction with the SNP Data Using HIBAG Package of Bioconductor and R Programming
The present study introduces Snips2HLA-HsG, an integrated application designed for SNP genotype analysis and HLA allele type prediction. Leveraging attribute bagging, a powerful ensemble classifier technique from the Bioconductor HIBAG package, Snips2HLA-HsG offers a comprehensive response for genetic analysis. Accessible via https://snips2hla.shinyapps.io/hla_home/, the application distinguishes itself by prioritizing user-friendliness and integrating all-purpose functionalities, including sample preparation, model generation, HLA prediction, and accuracy assessment. In contrast to the fragmented landscape of existing HLA imputation software, this study addresses the need for an integrated, user-centric platform. By streamlining processes and enhancing accessibility, Snips2HLA-HsG ensures usability, even for biologists with limited computer proficiency. Future updates will address the choice between one or ten classifiers, aiming to optimize server utility and meet research needs effectively by adding more classifiers to utilize multiple cores for faster calculations. Looking ahead, Snips2HLA-HsG will undergo regular updates and maintenance to ensure continued effectiveness and relevance in genetic research. Maintenance efforts will focus on resolving issues or bugs and providing ongoing user support.