'treeio' is an R package to make it easier to import and store phylogenetic tree with associated data; and to link external data from different sources to phylogeny. It also supports exporting phylogenetic tree with heterogeneous associated
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Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
BiocManager::install("treeio")treedata-book resource linked in the package stub.treedata-book website because the built-in vignette is only a stub.treeio focuses strictly on base classes for input and output.knitr::opts_chunk$set option used to control code formatting in the vignette.knitr::opts_chunk$set option used to suppress messages during document compilation.https://yulab-smu.top/treedata-book/ for the full vignette and comprehensive workflow instructions.tidy = FALSE and message = FALSE in knitr::opts_chunk$set when compiling reports to avoid clutter.treedata-book link provided in the vignette text.message = FALSE in the knitr::opts_chunk$set options.treeio offers specialized base classes for input and output.treeio is specifically designed for integration with the treedata-book ecosystem.treeio for tidy data manipulation rather than just input/output.This skill is the knowledge layer — when, why, and how to use treeio. 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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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
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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
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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
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