Address some of the reviewers' comments#80
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| yet flexible workflows. In particular, the direct interoperability with the | ||
| yet flexible workflows, as TreeSE inherits full compatibility with methods | ||
| designed for SE. In particular, the direct interoperability with the | ||
| widely adopted SE data science ecosystem distinguishes our TreeSE-based |
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This highlights that all methods that are using SE can be used with TreeSE.
We could consider highlighting SummarizedExperiment more (instead of TreeSE, we could talk about SE). It would emphasize that this framework is integrated to SE ecosystem
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Ehkä se olisi hyvä. Ja sit esitetään TreeSE laajennuksena siihen.
| omics data sets [@huber2015; @ramos2017; @amezquita2020]. By leveraging | ||
| standardized multi-assay data structures, users can apply a growing | ||
| number of integrative methods for multi-omics analysis. This eliminates the | ||
| need for manual data wrangling, reduces the risk of errors (*e.g.*, sample | ||
| mismatches), and enables the creation of modular, efficient, and reproducible | ||
| workflows. Such integrative approaches in microbiome |
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This highlights more the benefits of MultiAssayExperiment
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Could be added more examples on methods that are supporting MAE
| microbiome data [@benedetti2025]. The former extends iSEE to provide support for | ||
| TreeSE objects, while the latter builds on iSEEtree to enable analyses without | ||
| requiring any programming. Their interface supports automatic generation of | ||
| source code and replicable workflows as well as analysis templates for users | ||
| without a strong programming expertise. Moreover, the tidy R paradigm, available |
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Reviewer said that it is not clear how iSEEtree and miaDash relates to iSEE
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We can clarify that iSEEtree is a generic extension of iSEE for hierarchical data, whereas miaDash is a specific application of iSEEtree for code-free microbiome analysis.
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Can you @RiboRings suggest improvements to text once this PR is merged?
| microbiome data [@benedetti2025]. The former extends iSEE to provide support for | ||
| TreeSE objects, while the latter builds on iSEEtree to enable analyses without | ||
| requiring any programming. Their interface supports automatic generation of | ||
| source code and replicable workflows as well as analysis templates for users | ||
| without a strong programming expertise. Moreover, the tidy R paradigm, available |
| and application of modular, interoperable statistical workflows. Here we present | ||
| a R/Bioconductor ecosystem for microbiome data science. While TreeSE and MAE are | ||
| prior contributions, we have built an ecosystem around them through further | ||
| method and community development. We also provide a comprehensive online book |
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specifically serving the microbiome data science community
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Mihin kohtaan tämä oli? En saanut tätä sopimaan.
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Summary of things that need to be still refined:
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