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 fetches microarray data directly from GEO database, based on the GEOQuery R package. Given a GSE accession ID, it returns an Rdata object containing the data and a text file (.cond file) summarizing the conditions of the experimen
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Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
BiocManager::install("GEOquery")ExpressionSet using getGEO.searchGEO and searchFieldsGEO.getRNASeqData..mtx or .h5 files, BED files) attached to GEO records using getGEOSuppFiles.DropletUtils (e.g., read10xCounts) directly on your local files instead of routing through GEOquery."GSE2553"): The primary GEO accession string passed to getGEO or getGEOSuppFiles.TRUE): Forces getGEO to use the faster, tab-delimited GSEMatrix files instead of the legacy SOFT format.TRUE): Automatically includes GPL (Platform) annotation when retrieving GSE records.TRUE): When set to FALSE in getGEOSuppFiles, it lists available supplementary files without downloading them.getGEOSuppFiles to download only specific file types (e.g., 'txt').TRUE): Applies a log2 transformation when converting a GDS object to an ExpressionSet using GDS2eSet.GSEMatrix = TRUE (the default) when downloading GSEs, as parsing is 10-100x faster and memory usage is more efficient than legacy SOFT files.hasRNASeqQuantifications before attempting to download and process raw RNA-seq supplementary files.GDS2eSet (for ExpressionSet) or GDS2MA (for limma's MAList).getGSEDataTables to extract additional metadata tables that might not be captured in the standard GSE structure.getGEO returns a list of ExpressionSet objects because a single GSE can contain experiments from multiple platforms; fix this by indexing the list (e.g., gse[[1]]).getGEOSuppFiles on a large GSE can download gigabytes of unwanted data; fix this by running with fetch_files = FALSE first to inspect the file list..mtx file without barcodes and features; fix this by downloading the full tarball or all related supplementary files, then using DropletUtils::read10xCounts on the extracted prefix.DropletUtils: For reading the actual 10x single-cell files (read10xCounts) after GEOquery has downloaded them.limma: For downstream differential expression analysis of the ExpressionSet or MAList objects generated by GEOquery.This skill is the knowledge layer — when, why, and how to use geoquery. 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.
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 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.
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。
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).
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。
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。