Implements a variety of methods for combining p-values in differential analyses of genome-scale datasets. Functions can combine p-values across different tests in the same analysis (e.g., genomic windows in ChIP-seq, exons in RNA-seq) or fo
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Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
BiocManager::install("metapod")csaw) using grouped functions like groupedSimes.scran) using parallel functions like parallelSimes.summarizeParallelDirection or summarizeGroupedDirection.p.adjust instead because metapod is designed for hierarchical or multi-test aggregation.metapod operates strictly on p-values and their directions.grouped* functions) or a list of parallel numeric vectors of p-values (for parallel* functions).combineGroupedPValues (e.g., "simes", "holm-min").summarizeParallelDirection to only consider tests that contributed to the final p-value.parallelSimes or groupedSimes) when you expect dependencies between tests (e.g., overlapping genomic windows) as it is robust to such dependencies.log.p = TRUE when dealing with extremely small p-values to prevent underflow to zero during calculation.summarizeParallelDirection or summarizeGroupedDirection on the influential tests to avoid noise from non-significant tests when determining the consensus log-fold change direction.groupedFisher or parallelFisher) on highly correlated tests. Fix: Switch to Simes' method or the minimum Holm approach (groupedHolmMin), which do not require independence.log.p = TRUE.countParallelDirection without understanding that it applies Benjamini-Hochberg or Holm corrections internally. Fix: Read the documentation for countParallelDirection carefully, or use summarizeParallelDirection for a simpler consensus.This skill is the knowledge layer — when, why, and how to use metapod. 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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