The package xmapbridge can plot graphs in the X:Map genome browser. X:Map uses the Google Maps API to provide a scrollable view of the genome. It supports a number of species, and can be accessed at http://xmap.picr.man.ac.uk. This package exports plotting files in a suitable format. Graph plotting in R is done using calls to the functions xmap.plot and xmap.points, which have parameters that aim to be similar to those used by the standard plot methods in R. These result in data being written to a set of files (in a specific directory structure) that contain the data to be displayed, as well as some additional meta-data describing each of the graphs.

The ReportingTools package enables users to easily display reports of analysis results generated from sources such as microarray and sequencing data. The package allows users to create HTML pages that may be viewed on a web browser, or in other formats. Users can generate tables with sortable and filterable columns, make and display plots, and link table entries to other data sources such as NCBI or larger plots within the HTML page. Using the package, users can also produce a table of contents page to link various reports together for a particular project that can be viewed in a web browser.

This package comprises a set of pretrained machine learning models to predict basic immune cell types. This enables to quickly get a first annotation of the cell types present in the dataset without requiring prior knowledge. The package also lets you train using own models to predict new cell types based on specific research needs.

This package manages the installation of CMake for building Bioconductor packages. This avoids the need for end-users to manually install CMake on their system. No action is performed if a suitable version of CMake is already available.

This package provides functions to compare two or more survival curves with:

• The Fleming-Harrington test for right-censored data based on permutations and on counting processes.

• An extension of the Fleming-Harrington test for interval-censored data based on a permutation distribution and on a score vector distribution.

In order to assess the quality of a set of predicted genes for a genome, evidence must first be mapped to that genome. Next, each gene must be categorized based on how strong the evidence is for or against that gene. The AssessORF package provides the functions and class structures necessary for accomplishing those tasks, using proteomics hits and evolutionarily conserved start codons as the forms of evidence.

BANDITS is a Bayesian hierarchical model for detecting differential splicing of genes and transcripts, via DTU (differential transcript usage), between two or more conditions. The method uses a Bayesian hierarchical framework, which allows for sample specific proportions in a Dirichlet-Multinomial model, and samples the allocation of fragments to the transcripts. Parameters are inferred via MCMC (Markov chain Monte Carlo) techniques and a DTU test is performed via a multivariate Wald test on the posterior densities for the average relative abundance of transcripts.

RCAS aims to be a standalone RNA-centric annotation system that provides intuitive reports and publication-ready graphics. This package provides the R library implementing most of the pipeline's features.

Dirichlet-multinomial mixture models can be used to describe variability in microbial metagenomic data. This package is an interface to code originally made available by Holmes, Harris, and Quince, 2012, PLoS ONE 7(2): 1-15.

This package provides an implementation of an algorithm for recalibrating the base quality scores for aligned sequencing data in BAM format.

This package implements the unified Wilcoxon-Mann-Whitney Test for qPCR data. This modified test allows for testing differential expression in qPCR data.

This package provides a Poisson mixture model is implemented to cluster genes from high-throughput transcriptome sequencing (RNA-seq) data. Parameter estimation is performed using either the EM or CEM algorithm, and the slope heuristics are used for model selection (i.e., to choose the number of clusters).

This package defines a BigMatrix ReferenceClass which adds safety and convenience features to the filebacked.big.matrix class from the bigmemory package. BigMatrix protects against segfaults by monitoring and gracefully restoring the connection to on-disk data and it also protects against accidental data modification with a file-system-based permissions system. Utilities are provided for using BigMatrix-derived classes as assayData matrices within the Biobase package's eSet family of classes. BigMatrix provides some optimizations related to attaching to, and indexing into, file-backed matrices with dimnames. Additionally, the package provides a BigMatrixFactor class, a file-backed matrix with factor properties.

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

This package contains the Homo.sapiens object to access data from several related annotation packages.

r-circrnaprofiler is a computational framework for a comprehensive in silico analysis of circular RNA (circRNAs). This computational framework allows combining and analyzing circRNAs previously detected by multiple publicly available annotation-based circRNA detection tools. It covers different aspects of circRNAs analysis from differential expression analysis, evolutionary conservation, biogenesis to functional analysis.

This package provides raw beta values from 36 samples across 3 groups from Illumina 450k methylation arrays.

This package contains genome-wide annotations for Human, primarily based on mapping using Entrez Gene identifiers.

This package is a visualization and analysis toolbox for short time course data which includes dimensionality reduction, clustering, two-sample differential expression testing and gene ranking techniques. The package also provides methods for retrieving enriched pathways.

This package provides memory efficient string containers, string matching algorithms, and other utilities, for fast manipulation of large biological sequences or sets of sequences.

This package expands the usethis package with the goal of helping automate the process of creating R packages for Bioconductor or making them Bioconductor-friendly.

Single-cell RNA-seq (scRNA-seq) is widely used to investigate the composition of complex tissues since the technology allows researchers to define cell-types using unsupervised clustering of the transcriptome. However, due to differences in experimental methods and computational analyses, it is often challenging to directly compare the cells identified in two different experiments. scmap is a method for projecting cells from a scRNA-seq experiment onto the cell-types or individual cells identified in a different experiment.

The topGO package provides tools for testing gene ontology (GO) terms while accounting for the topology of the GO graph. Different test statistics and different methods for eliminating local similarities and dependencies between GO terms can be implemented and applied.

This package implements a method that aims to identify enhancers on large scale. The STARR-seq data consists of two sequencing datasets of the same targets in a specific genome. The input sequences show which regions where tested for enhancers. Significant enriched peaks i.e. a lot more sequences in one region than in the input where enhancers in the genomic DNA are, can be identified. So the approach pursued is to call peak every region in which there is a lot more (significant in a binomial model) STARR-seq signal than input signal and propose an enhancer at that very same position. Enhancers then are called weak or strong dependent of there degree of enrichment in comparison to input.