ToTem: a tool for variant calling pipeline optimization
High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Here we introduce ToTem, a tool for automated pipeline o...
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Published in: | BMC bioinformatics Vol. 19; no. 1; p. 243 |
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Abstract | High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall.
Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data.
ToTem is a tool for automated pipeline optimization which is freely available as a web application at https://totem.software . |
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AbstractList | Background High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Results Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. Conclusions ToTem is a tool for automated pipeline optimization which is freely available as a web application at Keywords: Variant calling, Benchmarking, Next generation sequencing, Parameter optimization High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. ToTem is a tool for automated pipeline optimization which is freely available as a web application at https://totem.software. BACKGROUNDHigh-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall.RESULTSHere we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data.CONCLUSIONSToTem is a tool for automated pipeline optimization which is freely available as a web application at https://totem.software . Abstract Background High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Results Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user’s priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. Conclusions ToTem is a tool for automated pipeline optimization which is freely available as a web application at https://totem.software. High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user's priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. ToTem is a tool for automated pipeline optimization which is freely available as a web application at https://totem.software . Background High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing appropriate tools and selecting the best parameters for optimal precision and recall. Results Here we introduce ToTem, a tool for automated pipeline optimization. ToTem is a stand-alone web application with a comprehensive graphical user interface (GUI). ToTem is written in Java and PHP with an underlying connection to a MySQL database. Its primary role is to automatically generate, execute and benchmark different variant calling pipeline settings. Our tool allows an analysis to be started from any level of the process and with the possibility of plugging almost any tool or code. To prevent an over-fitting of pipeline parameters, ToTem ensures the reproducibility of these by using cross validation techniques that penalize the final precision, recall and F-measure. The results are interpreted as interactive graphs and tables allowing an optimal pipeline to be selected, based on the user’s priorities. Using ToTem, we were able to optimize somatic variant calling from ultra-deep targeted gene sequencing (TGS) data and germline variant detection in whole genome sequencing (WGS) data. Conclusions ToTem is a tool for automated pipeline optimization which is freely available as a web application at https://totem.software. |
ArticleNumber | 243 |
Audience | Academic |
Author | Kubesova, Blanka Bystry, Vojtech Malcikova, Jitka Tom, Ondrej Pospisilova, Sarka Pavlova, Sarka Rausch, Tobias Kolarik, Miroslav Benes, Vladimir Tom, Nikola |
Author_xml | – sequence: 1 givenname: Nikola orcidid: 0000-0001-7440-0515 surname: Tom fullname: Tom, Nikola organization: Department of Internal Medicine - Hematology and Oncology, Medical Faculty, Masaryk University and University Hospital Brno, Brno, Czech Republic – sequence: 2 givenname: Ondrej surname: Tom fullname: Tom, Ondrej organization: Department of Computer Science, Faculty of Science, Palacky University, Olomouc, Czech Republic – sequence: 3 givenname: Jitka surname: Malcikova fullname: Malcikova, Jitka organization: Department of Internal Medicine - Hematology and Oncology, Medical Faculty, Masaryk University and University Hospital Brno, Brno, Czech Republic – sequence: 4 givenname: Sarka surname: Pavlova fullname: Pavlova, Sarka organization: Department of Internal Medicine - Hematology and Oncology, Medical Faculty, Masaryk University and University Hospital Brno, Brno, Czech Republic – sequence: 5 givenname: Blanka surname: Kubesova fullname: Kubesova, Blanka organization: Department of Internal Medicine - Hematology and Oncology, Medical Faculty, Masaryk University and University Hospital Brno, Brno, Czech Republic – sequence: 6 givenname: Tobias surname: Rausch fullname: Rausch, Tobias organization: Genomics Core Facility, European Molecular Biology Laboratory, Heidelberg, Germany – sequence: 7 givenname: Miroslav surname: Kolarik fullname: Kolarik, Miroslav organization: Department of Computer Science, Faculty of Science, Palacky University, Olomouc, Czech Republic – sequence: 8 givenname: Vladimir surname: Benes fullname: Benes, Vladimir organization: Genomics Core Facility, European Molecular Biology Laboratory, Heidelberg, Germany – sequence: 9 givenname: Vojtech surname: Bystry fullname: Bystry, Vojtech email: vojtech.bystry@ceitec.muni.cz organization: Center of Molecular Medicine, Central European Institute of Technology, Masaryk University, Brno, Czech Republic. vojtech.bystry@ceitec.muni.cz – sequence: 10 givenname: Sarka surname: Pospisilova fullname: Pospisilova, Sarka email: pospisilova.sarka@fnbrno.cz, pospisilova.sarka@fnbrno.cz organization: Department of Internal Medicine - Hematology and Oncology, Medical Faculty, Masaryk University and University Hospital Brno, Brno, Czech Republic. pospisilova.sarka@fnbrno.cz |
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Cites_doi | 10.1093/bioinformatics/btt750 10.1101/gr.129684.111 10.1038/ng.806 10.1038/leu.2017.230 10.1093/bib/bbs086 10.1002/0471250953.bi1110s43 10.1186/s13073-016-0269-0 10.1038/leu.2014.297 10.1038/nbt.2743 10.1038/srep17875 10.1093/bioinformatics/btu345 10.1101/023754 10.1038/nbt.2835 10.1093/bioinformatics/btu356 10.1038/sdata.2016.25 10.1093/bioinformatics/btp373 10.1093/bioinformatics/btp324 10.1093/bioinformatics/btw587 10.1038/srep14283 10.1093/nar/gkw227 10.1038/srep43169 10.1093/nar/gkw343 |
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Keywords | Benchmarking Parameter optimization Next generation sequencing Variant calling |
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Snippet | High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is choosing... Background High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is... BACKGROUNDHigh-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key problem is... Abstract Background High-throughput bioinformatics analyses of next generation sequencing (NGS) data often require challenging pipeline optimization. The key... |
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SubjectTerms | Analysis Artificial intelligence Automation Benchmarking Bioinformatics C plus plus Computational Biology - methods Computer graphics Data processing Gene sequencing Genomes Genomics Graphical user interface High-Throughput Nucleotide Sequencing - methods High-throughput screening (Biochemical assaying) Leukemia Mathematical functions Medical research Mutation Next generation sequencing Optimization Parameter estimation Parameter optimization Parameters Process controls Recall Reproducibility Reproducibility of Results Research Design Software Variant calling Web applications |
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Title | ToTem: a tool for variant calling pipeline optimization |
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