This package provides raw data objects to be used for blood cell proportion estimation in minfi and similar packages. The FlowSorted.Blood.EPIC object is based in samples assayed by Brock Christensen and colleagues; for details see Salas et al. 2018. https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE110554.

Bayesian network analysis is a form of probabilistic graphical models which derives from empirical data a directed acyclic graph, DAG, describing the dependency structure between random variables. An additive Bayesian network model consists of a form of a DAG where each node comprises a generalized linear model (GLM). Additive Bayesian network models are equivalent to Bayesian multivariate regression using graphical modelling, they generalises the usual multivariable regression, GLM, to multiple dependent variables. This package provides routines to help determine optimal Bayesian network models for a given data set, where these models are used to identify statistical dependencies in messy, complex data.

This package defines data structures for linkage disequilibrium (LD) measures in populations. Its purpose is to simplify handling of existing population-level data for the purpose of flexibly defining LD blocks.

This package provides C and C++ HDF5 libraries for use in R packages.

This package contains functions for the efficient design of factorial two-colour microarray experiments and for the statistical analysis of factorial microarray data.

The Seqinfo class stores the names, lengths, circularity flags, and genomes for a particular collection of sequences. These sequences are typically the chromosomes and/or scaffolds of a specific genome assembly of a given organism. Seqinfo objects are rarely used as standalone objects. Instead, they are used as part of higher-level objects to represent their seqinfo() component. Examples of such higher-level objects are GRanges, RangedSummarizedExperiment, VCF, GAlignments, etc… defined in other Bioconductor infrastructure packages.

This package provides the full genome sequences for Bos taurus (UCSC version bosTau8).

This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis.

This package provides a set of annotation maps for the REACTOME database, assembled using data from REACTOME.

This package provides S4 generic functions needed by many Bioconductor packages.

The biodb package provides access to standard remote chemical and biological databases (ChEBI, KEGG, HMDB, ...), as well as to in-house local database files (CSV, SQLite), with easy retrieval of entries, access to web services, search of compounds by mass and/or name, and mass spectra matching for LCMS and MSMS. Its architecture as a development framework facilitates the development of new database connectors for local projects or inside separate published packages.

This package provides methods to convert between Python AnnData objects and SingleCellExperiment objects. These are primarily intended for use by downstream Bioconductor packages that wrap Python methods for single-cell data analysis. It also includes functions to read and write H5AD files used for saving AnnData objects to disk.

This package implements an approach for scanning the genome to detect and perform accurate inference on differentially methylated regions from Whole Genome Bisulfite Sequencing data. The method is based on comparing detected regions to a pooled null distribution, that can be implemented even when as few as two samples per population are available. Region-level statistics are obtained by fitting a generalized least squares (GLS) regression model with a nested autoregressive correlated error structure for the effect of interest on transformed methylation proportions.

This package provides an expressionSet containing gene expression data from 60 bone marrow samples of patients with one of the four main types of leukemia (ALL, AML, CLL, CML) or non-leukemia.

This package provides a set of functions to create and interact with dynamic documents and vignettes.

This package implements the GENIE3 algorithm for inferring gene regulatory networks from expression data.

This package provides a test harness for bsseq loading of Biscuit output, summarization of WGBS data over defined regions and in mappable samples, with or without imputation, dropping of mostly-NA rows, age estimates, etc.

This package provides an interface to Affymetrix chip annotation and sample attribute files. The package allows an easy way for users to download and manage local data bases of Affynmetrix NetAffx annotation files. It also provides access to GeneChip Operating System (GCOS) and GeneChip Command Console (AGCC)-compatible sample annotation files.

This package provides a pipeline for the analysis of GRO-seq data.

XBSeq is a novel algorithm for testing RNA-seq differential expression (DE), where a statistical model was established based on the assumption that observed signals are the convolution of true expression signals and sequencing noises. The mapped reads in non-exonic regions are considered as sequencing noises, which follows a Poisson distribution. Given measurable observed signal and background noise from RNA-seq data, true expression signals, assuming governed by the negative binomial distribution, can be delineated and thus the accurate detection of differential expressed genes.

This package provides tools for analysis of ChIP-seq and other functional sequencing data.

This package provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.

This package provides processed and raw count data for single-cell RNA sequencing. In addition, this package offers single-cell ATAC-seq, and seqFISH (spatial transcriptomic) experiments performed along a timecourse of mouse gastrulation and early organogenesis.

This package creates karyotype plots of arbitrary genomes and offers a complete set of functions to plot arbitrary data on them. It mimics many R base graphics functions coupling them with a coordinate change function automatically mapping the chromosome and data coordinates into the plot coordinates.