TreeSummarizedExperiment has extended SingleCellExperiment to include hierarchical information on the rows or columns of the rectangular data.
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Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
BiocManager::install("TreeSummarizedExperiment")TreeSummarizedExperiment class.aggTSE.subsetByNode.referenceSeq slot.SingleCellExperiment because the tree-related slots and overhead are unnecessary.ape or ggtree directly because they are specialized for tree operations.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.phylo objects for rowTree and/or colTree.rowNodeLab or colNodeLab.DNAStringSet or DNAStringSetList.phylo object representing the hierarchical structure on the rows of the assays.rowTree.aggTSE, specified via node label or node number.sum) applied to the row dimension in aggTSE.findDescendant to specify if only leaf descendants should be returned.aggTSE when aggregating both dimensions.colData to keep in the final output of aggTSE.toTree to convert a taxonomic data.frame into a phylo object before adding it to the object.changeTree to replace an existing tree and update the mapping if nodes are labeled differently.aggTSE with colDataCols to speed up aggregation by dropping irrelevant column data.rowLinks or colLinks manually to prevent breaking the link between assays and trees.rowNodeLab or colNodeLab during construction.ape::keep.tip changes node numbers and breaks links. Fix: Use trackNode to track alias labels and update the LinkDataFrame accordingly.rowTree<- fails if names cannot be matched. Fix: Use changeTree with rowNodeLab when labels differ between the object and the new tree.TreeSummarizedExperiment relies on for plotting rather than implementing itself.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.
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概要と使いどころ
The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.
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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
日本語の概要は準備中です。原文の説明を表示しています。
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
日本語の概要は準備中です。原文の説明を表示しています。
apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.
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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).
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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
日本語の概要は準備中です。原文の説明を表示しています。