This is the core package for the automated analysis of Affymetrix arrays.

This package provides microarray data (from the Illumina Ref-8 BeadChips platform) and phenotype-level data from an epidemiological investigation of benzene exposure, packaged using SummarizedExperiemnt, for use as an example with the biotmle R package.

This package provides full genome sequences for Mus musculus (Mouse) as provided by UCSC (mm9, July 2007) and stored in Biostrings objects.

This is a package for significance analysis of Microarrays for differential expression analysis, RNAseq data and related problems.

The BADER package is intended for the analysis of RNA sequencing data. The algorithm fits a Bayesian hierarchical model for RNA sequencing count data. BADER returns the posterior probability of differential expression for each gene between two groups A and B. The joint posterior distribution of the variables in the model can be returned in the form of posterior samples, which can be used for further down-stream analyses such as gene set enrichment.

This package allows biologists to judge in the first place whether the sequence surrounding the polymorphism is a good match, and in the second place how much information is gained or lost in one allele of the polymorphism relative to another. This package gives a choice of algorithms for interrogation of genomes with motifs from public sources:

1. a weighted-sum probability matrix;

2. log-probabilities;

3. weighted by relative entropy.

This package can predict effects for novel or previously described variants in public databases, making it suitable for tasks beyond the scope of its original design. Lastly, it can be used to interrogate any genome curated within Bioconductor.

The motifStack package is designed for graphic representation of multiple motifs with different similarity scores. It works with both DNA/RNA sequence motifs and amino acid sequence motifs. In addition, it provides the flexibility for users to customize the graphic parameters such as the font type and symbol colors.

The bayNorm package is used for normalizing single-cell RNA-seq data. The main function is bayNorm, which is a wrapper function for gene specific prior parameter estimation and normalization. The input is a matrix of scRNA-seq data with rows different genes and columns different cells. The output is either point estimates from posterior (2D array) or samples from posterior (3D array).

This package provides full genome sequences for Homo sapiens (Human) as provided by NCBI (GRCh38, 2013-12-17) and stored in Biostrings objects.

This package provides a function to infer pathway activity from gene expression. It contains the linear model inferred in the publication "Perturbation-response genes reveal signaling footprints in cancer gene expression".

This package provides functions to detect and correct for batch effects in DNA methylation data. The core function is based on latent factor models and can also be used to predict missing values in any other matrix containing real numbers.

This package provides a method for finding an enrichment of cancer simple somatic mutations (SNVs and Indels) in functional elements across the human genome. ActiveDriverWGS detects coding and noncoding driver elements using whole genome sequencing data.

This package is used for the analysis of long-range chromatin interactions from 3C-seq assay.

The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.

This is an annotation package for Illumina's EPIC v2.0 methylation arrays. The version 2 covers more than 935K CpG sites in the human genome hg38. It is an update of the original EPIC v1.0 array (i.e., the 850K methylation array).

This package provides data from 3 technical replicates of the cell line GM12878 from the EPIC methylation array.

This package provides a multivariate inferential analysis method for detecting differentially expressed genes in gene expression data. It uses artificial components, close to the data's principal components but with an exact interpretation in terms of differential genetic expression, to identify differentially expressed genes while controlling the false discovery rate (FDR).

This package provides Bayesian PCA, Probabilistic PCA, Nipals PCA, Inverse Non-Linear PCA and the conventional SVD PCA. A cluster based method for missing value estimation is included for comparison. BPCA, PPCA and NipalsPCA may be used to perform PCA on incomplete data as well as for accurate missing value estimation. A set of methods for printing and plotting the results is also provided. All PCA methods make use of the same data structure (pcaRes) to provide a common interface to the PCA results.

This package provides a software suite for the automated analysis of Affymetrix arrays.

This package provides tools for finding bumps in genomic data in order to identify differentially methylated regions in epigenetic epidemiology studies.

ChemmineOB provides an R interface to a subset of cheminformatics functionalities implemented by the OpelBabel C++ project. OpenBabel is a free cheminformatics toolbox that includes utilities for structure format interconversions, descriptor calculations, compound similarity searching and more. ChemineOB aims to make a subset of these utilities available from within R. For non-developers, ChemineOB is primarily intended to be used from ChemmineR as an add-on package rather than used directly.

This package provides flexible, quantitative, and integrative genomic visualizations for publication-quality multi-panel figures.

This package is devoted to analyzing high-throughput data (e.g. gene expression microarray, DNA methylation microarray, RNA-seq) from complex tissues. Current functionalities include

1. detect cell-type specific or cross-cell type differential signals

2. tree-based differential analysis

3. improve variable selection in reference-free deconvolution

4. partial reference-free deconvolution with prior knowledge.

This is a package for semi-supervised isoform detection and annotation from both bulk and single-cell long read RNA-seq data. Flames provides automated pipelines for analysing isoforms, as well as intermediate functions for manual execution.