This is an R package for interfacing with the BIOM format. This package includes basic tools for reading biom-format files, accessing and subsetting data tables from a biom object (which is more complex than a single table), as well as limi
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Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
BiocManager::install("biomformat")read_biom().biom_data().SummarizedExperiment objects using biom_to_SummarizedExperiment().make_biom().as_tibble.biom().phyloseq or DESeq2 because biomformat is strictly an I/O and utility package.dada2 because biomformat operates on already-constructed contingency tables.make_biom(), a count matrix (features in rows, samples in columns) and optional data.frame objects for observation and sample metadata.make_biom().data.frame when using make_biom().make_biom().biom_data().biom_data().read_biom() which automatically detects and routes HDF5 files to read_hdf5_biom().as_tibble.biom() to convert data into a tidy long-format for downstream dplyr and purrr workflows.write_hdf5_biom() instead of write_biom() to avoid JSON serialization limits.biom_data() to inspect subsets.as(biom_data(x), "matrix").write_biom() fails due to JSON string limits; fix this by using write_hdf5_biom() for HDF5 format.phyloseq: Has many more utilities for interacting with and analyzing this kind of data.SummarizedExperiment: The standard Bioconductor container for rectangular feature-by-sample assay data (though biomformat interoperates with it).This skill is the knowledge layer — when, why, and how to use biomformat. 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。