This is a package for saving Bioconductor data structures into file artifacts, and loading them back into memory. This is a more robust and portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

This package is designed for visualization of RNA-related genomic features with respect to the landmarks of RNA transcripts, i.e., transcription starting site, start codon, stop codon and transcription ending site.

This package provides a database of PROVEAN/SIFT predictions for Homo sapiens dbSNP build 137.

This package provides high performance functions for row and column operations on sparse matrices. Currently, the optimizations are limited to data in the column sparse format.

This library contains functions that calculate various statistics of differential expression for microarray data, including t statistics, fold change, F statistics, SAM, moderated t and F statistics and B statistics. It also implements a new methodology called DEDS (Differential Expression via Distance Summary), which selects differentially expressed genes by integrating and summarizing a set of statistics using a weighted distance approach.

This package provides methods to infer clonal tree configuration for a population of cells using single-cell RNA-seq data (scRNA-seq), and possibly other data modalities. Methods are also provided to assign cells to inferred clones and explore differences in gene expression between clones. These methods can flexibly integrate information from imperfect clonal trees inferred based on bulk exome-seq data, and sparse variant alleles expressed in scRNA-seq data. A flexible beta-binomial error model that accounts for stochastic dropout events as well as systematic allelic imbalance is used.

This package provides a framework for the visualization of genome coverage profiles. It can be used for ChIP-seq experiments, but it can be also used for genome-wide nucleosome positioning experiments or other experiment types where it is important to have a framework in order to inspect how the coverage distributed across the genome.

This package provides R functions for common pre-processing steps that are applied on 1H-NMR data. It also provides a function to read the FID signals directly in the Bruker format.

This package provides S4 generic functions modeled after the matrixStats API for alternative matrix implementations. Packages with alternative matrix implementation can depend on this package and implement the generic functions that are defined here for a useful set of row and column summary statistics. Other package developers can import this package and handle a different matrix implementations without worrying about incompatibilities.

This package provides ChIP-seq data for demonstration purposes in the chromstaR package.

This package extends beachmat to support initialization of tatami matrices from HDF5-backed arrays. This allows C++ code in downstream packages to directly call the HDF5 C/C++ library to access array data, without the need for block processing via DelayedArray. Some utilities are also provided for direct creation of an in-memory tatami matrix from a HDF5 file.

This package can be used for the analysis of gene expression studies, especially the use of linear models for analysing designed experiments and the assessment of differential expression. The analysis methods apply to different technologies, including microarrays, RNA-seq, and quantitative PCR.

This package represents an integrative method of analyzing multi omics data that conducts enrichment analysis of annotated gene sets. ActivePathways uses a statistical data fusion approach, rationalizes contributing evidence and highlights associated genes, improving systems-level understanding of cellular organization in health and disease.

The purpose of biocViews is to create HTML pages that categorize packages in a Bioconductor package repository according to keywords, also known as views, in a controlled vocabulary.

This package provides a GUI for analysis of Affymetrix microarray gene expression data using the affy and limma packages.

This is a package for identification of metabolites using high precision mass spectrometry. MS peaks are used to derive a ranked list of sum formulae, alternatively for a given sum formula the theoretical isotope distribution can be calculated to search in MS peak lists.

This package provides tools for the identification of differentially expressed genes and estimation of the False Discovery Rate (FDR) using both the Significance Analysis of Microarrays (SAM) and the Empirical Bayes Analyses of Microarrays (EBAM).

ChemmineR is a cheminformatics package for analyzing drug-like small molecule data in R. It contains functions for efficient processing of large numbers of molecules, physicochemical/structural property predictions, structural similarity searching, classification and clustering of compound libraries with a wide spectrum of algorithms. In addition, it offers visualization functions for compound clustering results and chemical structures.

This package includes positive ionization mode data in NetCDF file format. Centroided subset from 200-600 m/z and 2500-4500 seconds. Data originally reported in "Assignment of Endogenous Substrates to Enzymes by Global Metabolite Profiling" Biochemistry; 2004; 43(45). It also includes detected peaks in an xcmsSet.

This package implements quantile smoothing. It contains a dataset used to produce human chromosomal ideograms for plotting purposes and a collection of arrays that contains data of chromosome 14 of 3 colorectal tumors. The package provides functions for painting chromosomal icons, chromosome or chromosomal idiogram and other types of plots. Quantsmooth offers options like converting chromosomal ids to their numeric form, retrieving the human chromosomal length from NCBI data, retrieving regions of interest in a vector of intensities using quantile smoothing, determining cytoband position based on the location of the probe, and other useful tools.

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

Basic4Cseq is an R package for basic filtering, analysis and subsequent visualization of 4C-seq data. Virtual fragment libraries can be created for any BSGenome package, and filter functions for both reads and fragments and basic quality controls are included. Fragment data in the vicinity of the experiment's viewpoint can be visualized as a coverage plot based on a running median approach and a multi-scale contact profile.

This package performs hybrid multiple testing that incorporates method selection and assumption evaluations into the analysis using EBP estimates obtained by Grenander density estimation. For instance, for 3-group comparison analysis, Hybrid Multiple testing considers EBPs as weighted EBPs between F-test and H-test with EBPs from Shapiro Wilk test of normality as weight. Instead of just using EBPs from F-test only or using H-test only, this methodology combines both types of EBPs through EBPs from Shapiro Wilk test of normality. This methodology uses then the law of total EBPs.

This package exposes an annotation database generated from Ensembl.