Implements the circular binary segmentation (CBS) algorithm to segment DNA copy number data and identify genomic regions with abnormal copy number.
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Package-intrinsic requirements from the Bioconductor landing page — reproduce in any R environment.
BiocManager::install("DNAcopy")segment() function.plot().smooth.CNA().PureCN because DNAcopy only segments total copy number.AneuFinder because DNAcopy assumes bulk-level signal distributions.copynumber because DNAcopy processes samples independently.CNA object using the CNA() function.Chromosome identifiers, and a vector of Position (map locations).data.type="logratio"."sdundo"): Method to get rid of unnecessary change-points due to local trends.3): The number of standard deviations used when undo.splits="sdundo" to remove splits."w", "s", "c", "p"): Determines the layout of the plot() function (e.g., whole genome, by chromosome, across studies, or ordered by plateau)."perm"): Method for p-value computation. The default is a faster hybrid approach, but full permutations can be forced.10000): Number of permutations used in the hybrid method.1): Controls the printing of progress during the segment() run.smooth.CNA() on your CNA object to mitigate the effect of single point outliers before running segment().undo.splits="sdundo" with undo.SD=3 in segment() to remove false-positive change-points caused by local data trends.subset.CNA() to subset by chromosome and sample so that segmentation does not have to be run on a whole data set at once.plot() with plot.type="p" to order segments by their chromosome means, helping to visually determine the plateaus for calling gains (e.g., 0.4) and losses (e.g., -0.6).undo.splits="sdundo" parameter in segment().p.method='perm', or reduce nperm.plot.type="s" to plot by chromosome within a study.This skill is the knowledge layer — when, why, and how to use dnacopy. 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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