Defines an S4 class for storing data from spatial -omics experiments. The class extends SingleCellExperiment to support storage and retrieval of additional information from spot-based and molecule-based platforms, including spatial coordina
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BiocManager::install("SpatialExperiment")SpatialExperiment() and imgData().splitAsBumpyMatrix() and the molecules() accessor.rotateImg() and mirrorImg().SingleCellExperiment instead because the spatial-specific slots like spatialCoords and imgData will remain empty and add unnecessary overhead.SpatialExperiment is designed to link assays (like counts) with spatial metadata.counts) representing gene expression across spatial locations.DataFrame of coordinates (e.g., x and y) for each spot or cell.SpatialImage objects within an imgData DataFrame.counts).colData fields correspond to spatial coordinates.DataFrame containing image metadata and SpatialImage objects.DataFrame containing spot- or cell-level metadata."sample_01"): A character string specifying the sample identifier.spatialCoords() and imgData() accessor functions instead of directly manipulating internal slots to maintain object integrity.TENxVisiumList() and import() from the VisiumIO package to automatically load outputs from Space Ranger.cbind() to avoid automatic index appending.sample_ids with non-unique values returns an error; fix this by ensuring replacement IDs map uniquely to existing ones.sample_id by setting it to NULL fails because it is a protected field; fix this by retaining the sample_id or replacing it with valid unique strings.spatialCoords and spatialCoordsNames causes spatialCoordsNames to be ignored; fix this by setting either to NULL to suppress the warning message.colData but lacks dedicated spatialCoords and imgData slots.This skill is the knowledge layer — when, why, and how to use spatialexperiment. 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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