topGO package provides tools for testing GO terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and
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Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
BiocManager::install("topGO")runTest function on gene lists derived from differential expression.elim, weight, or weight01.statistic = "ks") on gene scores rather than just binary gene lists.showSigOfNodes.clusterProfiler because topGO is strictly designed for GO graph topologies).gprofiler2 or enrichR because topGO builds complex local graph structures which takes more time).hgu95av2.db, or custom mappings read by readMappings).topDiffGenes).annFUN.db, annFUN.gene2GO, annFUN.org).runTest (e.g., "classic", "elim", "weight", "parentchild").runTest (e.g., "fisher", "ks", "t").genefilter before defining the gene universe to improve computational efficiency.classic vs elim) using GenTable to see how topology correction affects the significance of parent/child terms.inverseList to easily transform custom mappings from gene-to-GOs to GO-to-genes when preparing custom annotations.score to extract p-values from a topGOresult object for custom plotting or comparisons.topGO handles the ancestor propagation.allGenes list can be annotated to GO. Fix: Check the topGOdata summary to see the actual number of "feasible genes" used in the analysis.ks with parentchild). Fix: Consult the compatibility matrix and use supported combinations like elim with ks or classic with fisher.This skill is the knowledge layer — when, why, and how to use topgo. 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。