{"id":"9b12ceae-1e2c-4217-af3d-a9ed6b4c77b6","arxiv_id":"2412.02882","paper_version":2,"verdict":"CONDITIONAL","confidence":"MODERATE","novelty_score":6.0,"correctness_risk":"medium","formal_verification":"none","parameter_count":0,"one_line_summary":"iSEEtree is a new R Shiny app that adds interactive, visual exploration of TreeSummarizedExperiment hierarchical data to the iSEE ecosystem.","lead":"iSEEtree is a free R app that gives researchers a point-and-click interface for exploring hierarchical biological data, such as microbiome species trees. It lowers the coding barrier for interactive data exploration and extends existing Bioconductor tools.","discovery_kind":"new_application","skeptic_critique":{"model":"deepseek-v4-flash","headline":"New TreeSE panels' inheritance of iSEE dynamic linking and code tracking is asserted but not demonstrated; a single interaction test would verify the central explorer claim.","rationale":"The reader's weakest assumption—that iSEE's framework can be reliably extended to TreeSE so that inherited features (dynamic linking, code tracking, custom colouring) work correctly for hierarchical data—identifies the same load-bearing concern I find. I sharpen it to a concrete, testable feature: the new TreeSE-specific panels' participation in dynamic linking and code tracking. The paper asserts this inheritance without evidence, and the absence of a demonstration is particularly significant because the abstract and introduction emphasize 'interactive' exploration and 'expanding the interactive graphics capabilities' of iSEE. If these inherited features are not functional for the hierarchical panels, the central value proposition collapses. I considered the usability overclaim about 'no extensive knowledge of R programming' being contradicted by the Limitations, but that is an overstated description of the target user, not a technical flaw; the interactivity concern goes to the core of what the software does. The proposed test is straightforward: run the app, interact with a tree panel, and inspect the generated code. Because the software is publicly available and the community can run this check, a CONDITIONAL verdict is appropriate. The reader already chose CONDITIONAL, so my concern does not alter the verdict, but it specifies the condition that should be met before acceptance. No ad hominem or theatrical language is needed; the issue is simply that a central claim is unsupported by evidence in the manuscript.","tokens_in":5478,"tokens_out":3988,"duration_ms":37048,"concrete_test":"Install iSEEtree v1.0 from Bioconductor, load the Tengeler example dataset, and launch the app. In a Row tree panel, select a clade; verify that the selection is transmitted to an Abundance or Reduced dimension panel (dynamic linking). Then click the 'Generate R code' button and check that the emitted script includes the Row tree panel call and reproduces the same plot when rerun. If either check fails, the inherited interactivity claim for TreeSE panels is unsupported.","verdict_should_be":"UNCHANGED","load_bearing_attack":"The paper's central contribution is the claim that iSEEtree 'expands the interactive graphics capabilities of related work to hierarchical structures' by extending the iSEE framework to TreeSummarizedExperiment objects. A key supporting assertion appears in the Software Implementation section: 'our app inherits the complete array of primary and auxiliary functionality from this foundation, including ... dynamic linking between panels, interactive panel tours, custom panel colouring, code tracking for reproducibility and downloadable results.' This inheritance is claimed for the new TreeSE-specific panels (Abundance, Row tree, Column tree), yet no test or demonstration shows that these panels actually participate in dynamic linking, generate reproducible R code, or support panel tours. The only demonstration is a static screenshot (Fig. 1B). The Limitations section acknowledges restricted panel coverage and scalability, but does not address whether the inherited interactive features function for the hierarchical panels. If dynamic linking fails for these panels, the app becomes a collection of static plots rather than an interactive explorer, directly undermining the central claim of expanding iSEE to hierarchical structures. This concern is load-bearing because the contribution is precisely the interactive integration with TreeSE, not merely the existence of tree plots.","agreement_with_reader":"agree"},"referee_report":{"model":"deepseek-v4-flash","summary":"The paper presents iSEEtree, an R Shiny application built on the iSEE package that provides a graphical interface for exploring TreeSummarizedExperiment (TreeSE) objects. The central claim is that iSEEtree extends iSEE's interactive graphics to hierarchical data structures, enabling users to explore microbiome and other multi-table datasets through panels such as Abundance, Reduced dimension, Loading, Row tree, and Column tree without writing plotting code. The authors describe the workflow (import, construct TreeSE, launch app), list the panel types, and illustrate the interface with a screenshot from a mouse gut microbiome dataset (Tengeler et al., 2020). The paper also discusses related work, the TreeSE container, integration with the mia ecosystem (e.g., miaDash), and three limitations: scalability, restricted panel coverage, and the need to build TreeSE objects and launch the app from R or RStudio.","tokens_in":5753,"tokens_out":2925,"duration_ms":28234,"significance":"If the central claim holds, iSEEtree is a valuable contribution to the Bioconductor ecosystem because it lowers the technical barrier for exploring hierarchical data, particularly in microbiome research, and it provides a foundation for domain-specific graphical tools such as miaDash. The software is openly available on Bioconductor with documentation and a tutorial, which is a concrete strength. The paper convincingly argues that adopting the TreeSE container gives the tool broader applicability than phyloseq-based solutions. However, the paper overstates its case in two ways that affect the strength of the contribution: the abstract's 'without the need for extensive knowledge of R programming' is in tension with the Limitations section, and the claim that the new TreeSE-specific panels inherit iSEE's dynamic linking, code tracking, and tours is asserted but not demonstrated. These are fixable issues, but they are central to the paper's stated motivation.","major_comments":[{"comment":"The paragraph beginning 'Consequently, our app inherits the complete array...' asserts that the new TreeSE-specific panels (Abundance, Row tree, Column tree) inherit iSEE's dynamic linking, code tracking, panel tours, and downloadable results. This is load-bearing for the paper's central claim that iSEEtree 'expands the interactive graphics capabilities of related work to hierarchical structures.' Yet the manuscript provides no evidence that these interactive features actually work for the new panels: the only demonstration is a static screenshot (Fig. 1B), and the Limitations section does not address whether dynamic linking or code tracking function for hierarchical panels. If these features do not work, the app would be a collection of static plots rather than an interactive explorer. I ask the authors to provide a concrete demonstration—for example, a short reproducible example or animation showing a selection in the Row tree panel being reflected in an Abundance or Reduced dimension panel, and the corresponding R code generated by the 'code tracking' feature. Without such verification, the central claim is not yet established.","section":"Software Implementation"},{"comment":"The abstract and introduction state that users can 'interactively explore several aspects of their data without the need for extensive knowledge of R programming,' but the Limitations section says that 'it is still necessary to build TreeSE objects and launch the app either from R or RStudio' and that this 'may represent a barrier for novice users.' These statements are in tension: constructing TreeSE objects typically requires R programming, and launching from R/RStudio itself requires some R familiarity. The authors should either clarify that the intended user is someone who already works with R/Bioconductor and only needs to avoid writing plotting code, or soften the 'without the need' claim to 'with reduced need' or 'with minimal R knowledge.' As written, the motivation is undercut by the paper's own limitation.","section":"Abstract and Limitations"}],"minor_comments":[{"comment":"The text says the app is 'launched from an R console or RStudio by executing the command iSEE(tse),' but the package is named iSEEtree; please clarify whether this is a re-export of iSEE's function or a new function with the same name, to avoid confusion for users.","section":"Operative framework"},{"comment":"The phrase '16rRNA gene sequencing' should be corrected to '16S rRNA gene sequencing' for standard terminology.","section":"Applications / Use cases"},{"comment":"In Fig. 1B, the panel labels (i) through (vi) are referred to in the caption but the caption does not state which panel type corresponds to each label; adding explicit panel names (e.g., 'Abundance', 'Row tree', 'Reduced dimension') would make the figure self-contained.","section":"Figure 1"},{"comment":"The sentence 'However, certain panels require the presence of specific elements in the TreeSE object, and they will appear only when these are available' would benefit from a concrete example (e.g., RDA plot requires a reducedDim named 'RDA'), so that users know what to expect.","section":"Software Implementation"}],"recommendation":"major_revision","confidential_remarks":"The paper is a software applications note, and the software is real and installable. The main issue is evidential: the headline claim about expanding interactive graphics to hierarchical structures needs a positive demonstration of the inherited features on TreeSE-specific panels. This is not a fatal flaw—a short video, GIF, or reproducible R script showing cross-panel selection and code generation would suffice. I would not reject the paper, but I would not accept it in its current form because the central claim is under-supported. The tension with the Limitations section is also worth resolving. The paper fits the scope of an applications note in bioinformatics-oriented venues."},"author_rebuttal":null,"desk_editor":{"model":"deepseek-v4-flash","letter":"You should know this is a genuine software contribution, not vaporware. iSEEtree is on Bioconductor, the code is real, and the paper shows it adding hierarchical panels (Row tree, Column tree, Abundance) to the iSEE framework for TreeSummarizedExperiment objects. That combination is new, and for tool users in the microbiome/Bioconductor world it's a reasonable niche to fill. The paper describes the app clearly, documents its relationship to mia and iSEE, and demonstrates it on a real dataset. Credit where due: it's openly licensed, has online documentation, and is part of a larger ecosystem (miaDash) that actually uses it. No equations to check, but no invented claims either—the artifact is reproducible, and the citation pattern is honest, mostly to the packages it builds on.\n\nThe soft spots are real but not fatal. The abstract says users can explore 'without the need for extensive knowledge of R programming,' and the paper repeats that claim. Then the Limitations section says you still need to build TreeSE objects and launch the app from R or RStudio. That's a direct contradiction, and it should be fixed by toning down the 'no programming' language and instead saying 'lowered barrier' or 'no plotting code required after your TreeSE is ready.' Minor wording fix, but the paper's own text makes it hard to defend the headline.\n\nThe second, more substantive gap is the dynamic linking claim. The paper says iSEEtree 'inherits the complete array' of iSEE functionality, including dynamic linking, tours, code tracking, for the new panels. But no demonstration or test shows that the new tree and abundance panels actually participate in dynamic linking or emit reproducible code. The only evidence is a static screenshot. This is the central interactive claim, so it's worth probing. My guess is it probably works—the panels are built as iSEE panel classes, and iSEE's architecture is designed for that—but the paper doesn't prove it. An editor could reasonably ask for a short supplementary video, a worked example showing linked selections, or a vignette that exercises the code-tracking feature on the new panels. That would close the gap without requiring any new science.\n\nMinor quibble: no performance benchmarks, but the Limitations section acknowledges scaling limits, so that's consistent. The paper is a typical application note: modest scope, honest about constraints except for the one overclaim.\n\nBottom line: I'd send it to peer review. It's a real tool that a chunk of the community will use, and the issues are addressable with edits and a small verification step. My own verdict would be 'conditional accept' with the usability language fixed and the interactive claim demonstrated. Worth a reading group if anyone in your group works on microbiome viz or Shiny-based tools.","headline":"A real, installable iSEE extension for TreeSE data whose interactive integration is asserted more than demonstrated, and whose 'no programming' claim is undercut by its own Limitations section—still worth a proper referee.","tokens_in":6186,"tokens_out":1108,"would_cite":true,"duration_ms":13036,"reading_group":"maybe","serious_thinker":"yes","would_accept_peer_review":true},"rs_alignment":null,"lean_confirmation":null,"pith_extraction":{"msc":[],"pacs":[],"model":"deepseek-v4-flash","headline":"iSEEtree provides a visual interface for exploring hierarchical TreeSummarizedExperiment objects, letting users analyse microbiome data without writing R code.","keywords":["interactive visualization","hierarchical data","TreeSummarizedExperiment","microbiome analysis","R Shiny","ordination","data exploration","reproducibility"],"falsifier":"Open a TreeSE object with a large row tree in iSEEtree, select one clade in the Row tree panel, and check whether the linked abundance and heatmap panels update exactly to the members of that clade; if the selection mismatches or the app freezes, the claim that it provides reliable interactive hierarchical exploration fails.","tokens_in":5266,"feed_emoji":"🌳","tokens_out":5271,"duration_ms":45228,"temperature":0.7,"pith_summary":"The paper introduces iSEEtree, an R Shiny app that gives researchers a point-and-click interface for exploring TreeSummarizedExperiment objects, which store multi-table data together with hierarchical trees. The aim is to lower the programming barrier for analysing hierarchical data such as microbiome taxonomic tables. If the paper is right, users can visually inspect abundance, ordination, and tree structure without writing R code, while still inheriting iSEE's dynamic linking and reproducibility features. The authors demonstrate the app on a gut microbiome dataset and argue that the same generic panels apply to any hierarchical multi-table dataset.","feed_headline":"iSEEtree adds point-and-click trees to microbiome data exploration","feed_subtitle":"An R Shiny interface wraps TreeSummarizedExperiment objects in linked, interactive plots.","key_machinery":"The central object is the TreeSummarizedExperiment (TreeSE) container, an S4 class that extends SummarizedExperiment and SingleCellExperiment with rowTree, colTree, rowLinks, and colLinks elements to represent hierarchical relations among features and samples. The app's interface is built on the iSEE panel framework, which provides dynamic linking between panels, selectable parameters, and code tracking. iSEEtree adds hierarchical-aware panels to that framework, so the machinery carrying the argument is the combination of a standardized hierarchical data container with a proven interactive plotting engine.","core_discovery":"iSEEtree is an R Shiny application that extends the interactive exploration model of iSEE to TreeSummarizedExperiment objects. It adds custom panels for abundance barplots and density plots, reduced-dimension and RDA plots, loading plots, and row and column tree visualisations, all connected through iSEE's dynamic selection system. The paper reports that the app inherits the full iSEE feature set, including linked panels, code tracking for reproducibility, interactive tours, custom colouring, and downloadable plots, and demonstrates the workflow on a microbiome dataset derived from Tengeler et al. (2020). Its central contribution is a general-purpose, graphical front end for hierarchical data stored in the TreeSE container.","pith_inferences":["The paper does not test this, but the same panel framework could plausibly be applied to other TreeSE use cases, such as single-cell lineage trees or gene-family trees in comparative genomics, wherever a hierarchical grouping of rows or columns exists.","Because the limitations section names scalability as a concern, a natural stress test would compare iSEEtree's response time with command-line plotting on the same large TreeSE object to quantify the interaction overhead.","The code-tracking feature may lower the barrier to reproducible analysis for beginners, turning clicks into documented scripts that can later be edited by hand, though the paper does not evaluate this educational effect.","If the interface were extended to support constructing TreeSE objects directly, as the limitations suggest, the tool would become accessible to an even broader audience than the current R-based launch workflow allows."],"forward_implications":["Users can explore abundance, ordination, loading, and tree views side by side, with selections in one panel dynamically linked to the others.","The generated R scripts from an interactive session support reproducible reporting, turning clicks into documented analysis steps.","Because the app is built on the generic TreeSE container, the same panels should work for any hierarchical multi-table dataset, not only microbiome count tables.","The paper reports that iSEEtree already underpins a fully graphical web app for importing, manipulating, and visualising microbiome data, extending the same interface to users who do not use R directly.","Novice R users can perform compositional and ordination exploration without learning the underlying plotting commands."],"supporting_citations":[{"why":"Provides the iSEE interactive panel framework whose dynamic linking and panel system iSEEtree extends to hierarchical data.","marker":"Rue-Albrecht et al., 2018"},{"why":"Defines TreeSummarizedExperiment, the data container that iSEEtree is built around and which supplies rowTree and colTree slots.","marker":"Huang et al., 2020"},{"why":"Supplies the Shiny web application framework on which iSEEtree's interface is implemented.","marker":"Chang et al., 2024"},{"why":"Provides the mia package's microbiome analysis functions and TreeSE utilities that iSEEtree relies on for data handling and transformations.","marker":"Borman et al., 2024"},{"why":"Defines the SummarizedExperiment superclass that TreeSE extends, giving iSEEtree its assay and metadata structures.","marker":"Morgan et al., 2024"},{"why":"Introduces the SingleCellExperiment class and reducedDim slot that TreeSE inherits and that iSEEtree's reduced-dimension panels draw on.","marker":"Amezquita et al., 2020"},{"why":"Presents Shiny-phyloseq, an earlier interactive microbiome tool based on a different object class, serving as a contrast for iSEEtree's TreeSE-based generality.","marker":"McMurdie and Holmes, 2015"},{"why":"Presents animalcules, another package-specific interactive microbiome explorer, used as a comparison point for the field's existing solutions.","marker":"Zhao et al., 2021"},{"why":"Supplies the ADHD gut microbiome dataset used to demonstrate iSEEtree's workflow and panel layout.","marker":"Tengeler et al., 2020"}],"fun_headline_variants":["Point-and-click exploration for phylogenetic tree data","iSEEtree: interactive trees without R coding","Zero-code interface for hierarchical omics data","Drag-and-drop microbial tree analysis with R Shiny"],"cache_read_input_tokens":3200,"weakest_assumption_plain":"The central assumption is that iSEE's interactive panel machinery works reliably when extended to TreeSummarizedExperiment objects, so that linked selections and visualisations behave correctly on hierarchical data.","fun_headline_variants_meta":{"raw":{"variants":["Point-and-click exploration for phylogenetic tree data","iSEEtree: interactive trees without R coding","Zero-code interface for hierarchical omics data","Drag-and-drop microbial tree analysis with R Shiny"]},"model":"deepseek-v4-flash","effort":"low","cost_usd":0.000201,"raw_usage":{"total_tokens":1366,"prompt_tokens":922,"completion_tokens":444,"prompt_tokens_details":{"cached_tokens":384},"prompt_cache_hit_tokens":384,"prompt_cache_miss_tokens":538,"completion_tokens_details":{"reasoning_tokens":386}},"tokens_in":538,"tokens_out":444,"duration_ms":5697,"temperature":1.0,"reasoning_tokens":386,"cache_read_input_tokens":384,"cache_creation_input_tokens":0},"cache_creation_input_tokens":0},"created_at":"2026-08-11T22:58:32.724719+00:00","model_set":{"reader":"deepseek-v4-flash"},"falsifier":"Open a TreeSE object with a large row tree in iSEEtree, select one clade in the Row tree panel, and check whether the linked abundance and heatmap panels update exactly to the members of that clade; if the selection mismatches or the app freezes, the claim that it provides reliable interactive hierarchical exploration fails.","supporting_citations":[{"cited_title":"isee: interactive summarizedexperiment explorer","cited_arxiv_id":null,"evidence_quote":"Provides the iSEE interactive panel framework whose dynamic linking and panel system iSEEtree extends to hierarchical data."},{"cited_title":"Treesummarizedexperiment: a s4 class for data with hierarchical structure","cited_arxiv_id":null,"evidence_quote":"Defines TreeSummarizedExperiment, the data container that iSEEtree is built around and which supplies rowTree and colTree slots."},{"cited_title":"shiny: Web Application Framework for R, 2024","cited_arxiv_id":null,"evidence_quote":"Supplies the Shiny web application framework on which iSEEtree's interface is implemented."},{"cited_title":"Ernst, Sudarshan A","cited_arxiv_id":null,"evidence_quote":"Provides the mia package's microbiome analysis functions and TreeSE utilities that iSEEtree relies on for data handling and transformations."},{"cited_title":"SummarizedExperiment: SummarizedExperiment container, 2024","cited_arxiv_id":null,"evidence_quote":"Defines the SummarizedExperiment superclass that TreeSE extends, giving iSEEtree its assay and metadata structures."},{"cited_title":"Orchestrating single-cell analysis with bioconductor","cited_arxiv_id":null,"evidence_quote":"Introduces the SingleCellExperiment class and reducedDim slot that TreeSE inherits and that iSEEtree's reduced-dimension panels draw on."},{"cited_title":"Shiny-phyloseq: Web application for interactive microbiome analysis with provenance tracking","cited_arxiv_id":null,"evidence_quote":"Presents Shiny-phyloseq, an earlier interactive microbiome tool based on a different object class, serving as a contrast for iSEEtree's TreeSE-based generality."},{"cited_title":"Evan Johnson","cited_arxiv_id":null,"evidence_quote":"Presents animalcules, another package-specific interactive microbiome explorer, used as a comparison point for the field's existing solutions."},{"cited_title":"Gut microbiota from persons with attention-deficit/hyperactivity disorder affects the brain in mice","cited_arxiv_id":null,"evidence_quote":"Supplies the ADHD gut microbiome dataset used to demonstrate iSEEtree's workflow and panel layout."}],"review_version":1}