Harmonize data management of multiple experimental assays performed on an overlapping set of specimens. It provides a familiar Bioconductor user experience by extending concepts from SummarizedExperiment, supporting an open-ended mix of st
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Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
BiocManager::install("MultiAssayExperiment")sampleMap.[, intersectColumns, or intersectRows.longFormat or wideFormat.SummarizedExperiment instead.list or ExperimentList containing assay datasets (e.g., matrix, SummarizedExperiment, RangedSummarizedExperiment, RaggedExperiment).DataFrame containing primary patient/specimen metadata, where rownames are patient identifiers.DataFrame (assay, primary, colname) that unambiguously maps experimental observations to rows in colData.MultiAssayExperiment constructor.DataFrame of primary metadata describing the biological units (e.g., patients).DataFrame relating the primary data to the experimental assays.prepMultiAssay helper function before constructing the object to diagnose and resolve inconsistent names between the ExperimentList, colData, and sampleMap.listToMap convenience function to easily convert a list of platform-specific data frames into a valid sampleMap.metadata slot at the MultiAssayExperiment level.ExperimentList are named; unnamed elements will prompt an error during construction.prepMultiAssay causes an error. Fix: Assign names to the list elements (e.g., names(objlist) <- c("Affy", "Methyl")) before construction.colData via the sampleMap are silently dropped. Fix: Check the $drops element returned by prepMultiAssay to identify and fix unmatched identifiers.sampleMap without the exact column names assay, primary, and colname. Fix: Ensure the sampleMap strictly adheres to this three-column naming convention.This skill is the knowledge layer — when, why, and how to use multiassayexperiment. 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
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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
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。