With the dedicated fortify method implemented for flowSet, ncdfFlowSet and GatingSet classes, both raw and gated flow cytometry data can be plotted directly with ggplot. The ggcyto wrapper and some custom layers also make it easy to add gates and population statistics to the plot.

This package implements a method to rapidly assess cell type identity using both functional and random gene sets and it allows users to quantify cell type replicability across datasets using neighbor voting. MetaNeighbor works on the basis that cells of the same type should have more similar gene expression profiles than cells of different types.

This package provides routines for parsing Affymetrix data files based upon file format information. The primary focus is on accessing the CEL and CDF file formats.

This package provides tools for normalizing and analyzing of GeneChip Mapping 100K and 500K Set. Affymetrix GeneChip Human Mapping 100K and 500K Set allows the DNA copy number mea- surement of respectively 2× 50K and 2× 250K SNPs along the genome. Their high density allows a precise localization of genomic alterations and makes them a powerful tool for cancer and copy number polymorphism study.

The package AlphaBeta is a computational method for estimating epimutation rates and spectra from high-throughput DNA methylation data in plants. The method has been specifically designed to:

• analyze germline epimutations in the context of multi-generational mutation accumulation lines;

• analyze somatic epimutations in the context of plant development and aging.

The aim of TCGAbiolinks is:

1. facilitate GDC open-access data retrieval;

2. prepare the data using the appropriate pre-processing strategies;

3. provide the means to carry out different standard analyses, and;

4. to easily reproduce earlier research results.

In more detail, the package provides multiple methods for analysis (e.g., differential expression analysis, identifying differentially methylated regions) and methods for visualization (e.g., survival plots, volcano plots, starburst plots) in order to easily develop complete analysis pipelines.

This package provides example datasets that represent 'real world examples' of Affymetrix data, unlike the artificial examples included in the package affy.

This package provides an R interface to libsbml for SBML parsing, validating output, provides an S4 SBML DOM, converts SBML to R graph objects.

Analyze and visualize Mutation Annotation Format (MAF) files from large scale sequencing studies. This package provides various functions to perform most commonly used analyses in cancer genomics and to create feature rich customizable visualzations with minimal effort.

This package provides Affymetrix HG_U95Av2 Array annotation data (chip hgu95av2) assembled using data from public repositories.

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 AMARETTO represents an algorithm that integrates copy number, DNA methylation and gene expression data to identify a set of driver genes by analyzing cancer samples and connects them to clusters of co-expressed genes, which we define as modules. AMARETTO can be applied in a pancancer setting to identify cancer driver genes and their modules on multiple cancer sites. AMARETTO captures modules enriched in angiogenesis, cell cycle and EMT, and modules that accurately predict survival and molecular subtypes. This allows AMARETTO to identify novel cancer driver genes directing canonical cancer pathways.

This package translates bedtools command-line invocations to R code calling functions from the Bioconductor *Ranges infrastructure. This is intended to educate novice Bioconductor users and to compare the syntax and semantics of the two frameworks.

seqLogo takes the position weight matrix of a DNA sequence motif and plots the corresponding sequence logo as introduced by Schneider and Stephens (1990).

This package provides tools For analyzing Illumina Infinium DNA methylation arrays. SeSAMe provides utilities to support analyses of multiple generations of Infinium DNA methylation BeadChips, including preprocessing, quality control, visualization and inference. SeSAMe features accurate detection calling, intelligent inference of ethnicity, sex and advanced quality control routines.

Expedite large RNA-Seq analyses using a combination of previously developed tools. YARN is meant to make it easier for the user in performing basic mis-annotation quality control, filtering, and condition-aware normalization. YARN leverages many Bioconductor tools and statistical techniques to account for the large heterogeneity and sparsity found in very large RNA-seq experiments.

This package r-chromvar determines variation in chromatin accessibility across sets of annotations or peaks. r-chromvar is designed primarily for single-cell or sparse chromatin accessibility data like single cell assay for transposase-accessible chromatin using sequencing (scATAC-seq or sparse bulk ATAC or deoxyribonuclease sequence (DNAse-seq) experiments.

r-kegggraph is an interface between Kegg Pathway database and graph object as well as a collection of tools to analyze, dissect and visualize these graphs. It parses the regularly updated kgml (Kegg XML) files into graph models maintaining all essential pathway attributes. The package offers functionalities including parsing, graph operation, visualization and etc.

The package r-alevinqc generates quality control reports summarizing the output from an alevin run. The reports can be generated as HTML or PDF files, or as Shiny applications.

This package provides basic functions for filtering genes from high-throughput sequencing experiments.

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.

SGSeq is a package for analyzing splice events from RNA-seq data. Input data are RNA-seq reads mapped to a reference genome in BAM format. Genes are represented as a splice graph, which can be obtained from existing annotation or predicted from the mapped sequence reads. Splice events are identified from the graph and are quantified locally using structurally compatible reads at the start or end of each splice variant. The software includes functions for splice event prediction, quantification, visualization and interpretation.

This package provides a set of tools for making TxDb objects from genomic annotations from various sources (e.g. UCSC, Ensembl, and GFF files). These tools allow the user to download the genomic locations of transcripts, exons, and CDS, for a given assembly, and to import them in a TxDb object. TxDb objects are implemented in the GenomicFeatures package, together with flexible methods for extracting the desired features in convenient formats.

Volcano plots represent a useful way to visualise the results of differential expression analyses. This package provides a highly-configurable function that produces publication-ready volcano plots. EnhancedVolcano will attempt to fit as many point labels in the plot window as possible, thus avoiding clogging up the plot with labels that could not otherwise have been read. Other functionality allows the user to identify up to 4 different types of attributes in the same plot space via color, shape, size, and shade parameter configurations.