iSEEtree: interactive explorer for hierarchical data
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arXiv
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| Auteurs principaux: | , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866912144866410496 |
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| author | Benedetti, Giulio Seraidarian, Ely Pralas, Theotime Jeba, Akewak Borman, Tuomas Lahti, Leo |
| author_facet | Benedetti, Giulio Seraidarian, Ely Pralas, Theotime Jeba, Akewak Borman, Tuomas Lahti, Leo |
| contents | $\textbf{Motivation:}$ Hierarchical data structures are prevalent across several fields of research, as they represent an organised and efficient approach to study complex interconnected systems. Their significance is particularly evident in microbiome analysis, where microbial communities are classified at various taxonomic levels along the phylogenetic tree. In light of this trend, the R/Bioconductor community has established a reproducible analytical framework for hierarchical data, which relies on the highly generic and optimised TreeSummarizedExperiment data container. However, using this framework requires basic proficiency in programming.
$\textbf{Results:}$ To reduce the entry requirements, we developed iSEEtree, an R shiny app which provides a visual interface for the analysis and exploration of TreeSummarizedExperiment objects, thereby expanding the interactive graphics capabilities of related work to hierarchical structures. This way, users can interactively explore several aspects of their data without the need for extensive knowledge of R programming. We describe how iSEEtree enables the exploration of hierarchical multi-table data and demonstrate its functionality with applications to microbiome analysis.
$\textbf{Availability and Implementation:}$ iSEEtree was implemented in the R programming language and is available on Bioconductor at https://bioconductor.org/packages/iSEEtree under an Artistic 2.0 license.
$\textbf{Contact:}$ giulio.benedetti@utu.fi or leo.lahti@utu.fi. |
| format | Preprint |
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arxiv_https___arxiv_org_abs_2412_02882 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | iSEEtree: interactive explorer for hierarchical data Benedetti, Giulio Seraidarian, Ely Pralas, Theotime Jeba, Akewak Borman, Tuomas Lahti, Leo Mathematical Software Graphics Genomics G.4, H.5.2 $\textbf{Motivation:}$ Hierarchical data structures are prevalent across several fields of research, as they represent an organised and efficient approach to study complex interconnected systems. Their significance is particularly evident in microbiome analysis, where microbial communities are classified at various taxonomic levels along the phylogenetic tree. In light of this trend, the R/Bioconductor community has established a reproducible analytical framework for hierarchical data, which relies on the highly generic and optimised TreeSummarizedExperiment data container. However, using this framework requires basic proficiency in programming. $\textbf{Results:}$ To reduce the entry requirements, we developed iSEEtree, an R shiny app which provides a visual interface for the analysis and exploration of TreeSummarizedExperiment objects, thereby expanding the interactive graphics capabilities of related work to hierarchical structures. This way, users can interactively explore several aspects of their data without the need for extensive knowledge of R programming. We describe how iSEEtree enables the exploration of hierarchical multi-table data and demonstrate its functionality with applications to microbiome analysis. $\textbf{Availability and Implementation:}$ iSEEtree was implemented in the R programming language and is available on Bioconductor at https://bioconductor.org/packages/iSEEtree under an Artistic 2.0 license. $\textbf{Contact:}$ giulio.benedetti@utu.fi or leo.lahti@utu.fi. |
| title | iSEEtree: interactive explorer for hierarchical data |
| topic | Mathematical Software Graphics Genomics G.4, H.5.2 |
| url | https://arxiv.org/abs/2412.02882 |