跳到正文
cccskills
免费在 GitHub 公开

bioconductor-treesummarizedexperiment

TreeSummarizedExperiment has extended SingleCellExperiment to include hierarchical information on the rows or columns of the rectangular data.

中文简介正在准备中。当前显示原文说明。

查看安装方法

包含的文件(1)

  • SKILL.md5.4 KB

SKILL.md(原文)

安装前可以查看交给 AI 代理的指令内容。

TreeSummarizedExperiment

Dependencies & Environment

Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.

  • Version: 2.20.0 · Bioconductor: 3.23 · R: ≥ 4.6
  • Depends: SingleCellExperiment, S4Vectors, Biostrings
  • Imports: BiocGenerics, ape, rlang, dplyr, SummarizedExperiment, BiocParallel, IRanges, treeio
  • System requirements: URL
  • Install: BiocManager::install("TreeSummarizedExperiment")

When to Use

  • Storing rectangular experimental data alongside hierarchical tree structures using the TreeSummarizedExperiment class.
  • Aggregating data to different taxonomic levels (e.g., phylum or class) using aggTSE.
  • Subsetting data by specific tree nodes or leaves using subsetByNode.
  • Storing reference sequence data per feature using the referenceSeq slot.

When NOT to Use

  • For standard single-cell RNA-seq without hierarchical relationships, use SingleCellExperiment because the tree-related slots and overhead are unnecessary.
  • For purely manipulating or visualizing phylogenetic trees without rectangular assay data, use ape or ggtree directly because they are specialized for tree operations.

Data Requirements

  • An assays matrix representing observed data (e.g., counts) with rows as entities and columns as samples.
  • rowData and colData data frames for feature and sample annotations.
  • Hierarchical structures provided as phylo objects for rowTree and/or colTree.
  • Link information mapping assay rows/columns to tree nodes via rowNodeLab or colNodeLab.
  • Optional reference sequences as DNAStringSet or DNAStringSetList.

Key Parameters

  • rowTree: A phylo object representing the hierarchical structure on the rows of the assays.
  • rowNodeLab: A character vector linking the rows of the assays to the node labels of the rowTree.
  • colLevel: The desired aggregation level for columns in aggTSE, specified via node label or node number.
  • rowFun: The aggregate function (e.g., sum) applied to the row dimension in aggTSE.
  • only.leaf (TRUE): Logical in findDescendant to specify if only leaf descendants should be returned.
  • rowFirst (FALSE): Determines the aggregation order in aggTSE when aggregating both dimensions.
  • colDataCols: Specifies which columns of colData to keep in the final output of aggTSE.

Best Practices

  • Use toTree to convert a taxonomic data.frame into a phylo object before adding it to the object.
  • Use changeTree to replace an existing tree and update the mapping if nodes are labeled differently.
  • Use aggTSE with colDataCols to speed up aggregation by dropping irrelevant column data.
  • Avoid modifying rowLinks or colLinks manually to prevent breaking the link between assays and trees.

Common Pitfalls

  • Missing node labels: Row or column names in the assay do not match the node labels of the tree, causing them to be removed with warnings. Fix: Provide the correct mapping via rowNodeLab or colNodeLab during construction.
  • Broken links after pruning: Subsetting a tree with ape::keep.tip changes node numbers and breaks links. Fix: Use trackNode to track alias labels and update the LinkDataFrame accordingly.
  • Failed tree replacement: Replacing a tree directly with rowTree<- fails if names cannot be matched. Fix: Use changeTree with rowNodeLab when labels differ between the object and the new tree.

Alternatives

  • SingleCellExperiment: For storing single-cell data without hierarchical tree structures.
  • ape: For general phylogenetic tree manipulation without associated rectangular assay data.
  • ggtree: For visualizing phylogenetic trees, which TreeSummarizedExperiment relies on for plotting rather than implementing itself.

Citations

  • Huang R, et al. (2021). TreeSummarizedExperiment: a S4 class for data with tree structures. F1000Research.
  • Lun and Risso (2020). SingleCellExperiment.

References

<!-- biomate-cta -->

Run this on BioMate

This skill is the knowledge layer — when, why, and how to use treesummarizedexperiment. To run this analysis on your own data with managed compute, automated QC, and reproducible outputs, use BioMate — free to start.

▶ Open treesummarizedexperiment on BioMate →

评价

还没有评价。欢迎分享你的使用感受。

评论

无需登录即可发表。欢迎分享使用感受、提问,或说明在哪些环境下无法运行。

还没有评论。来写第一条吧。

提交后会立即公开。请勿填写邮箱、电话等个人信息。URL 最多 2 个。

0 / 1000 字

此表单受 reCAPTCHA 保护,适用 Google 的隐私权政策和服务条款。

同一仓库的技能

The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.

中文简介正在准备中。当前显示原文说明。

bioMate-AI/biomate-bioconductor-kb7932026年6月21日 更新

This tool uses the label-tree function from HyPhy to annotate a phylogenetic tree. It allows users to select a subset of leaves using either a regular expression or a list of sequence names, and then apply a specified label to these selecte

中文简介正在准备中。当前显示原文说明。

bioMate-AI/biomate-bioconductor-kb7932026年6月21日 更新

This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, En

中文简介正在准备中。当前显示原文说明。

bioMate-AI/biomate-bioconductor-kb7932026年6月21日 更新

apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.

中文简介正在准备中。当前显示原文说明。

bioMate-AI/biomate-bioconductor-kb7932026年6月21日 更新

ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).

中文简介正在准备中。当前显示原文说明。

bioMate-AI/biomate-bioconductor-kb7932026年6月21日 更新

AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched with

中文简介正在准备中。当前显示原文说明。

bioMate-AI/biomate-bioconductor-kb7932026年6月21日 更新

查看 bioMate-AI 的全部技能

报告此技能的问题