rGenomeTracks package leverages the power of pyGenomeTracks software with the interactivity of R. pyGenomeTracks is a python software that offers robust method for visualizing epigenetic data files like narrowPeak, Hic matrix, TADs and arcs, however though, here is no way currently to use it within R interactive session. rGenomeTracks wrapped the whole functionality of pyGenomeTracks with additional utilites to make to more pleasant for R users.

Codelink Rat Whole Genome Bioarray (~34 000 rat gene targets) annotation data (chip rwgcod) assembled using data from public repositories.

rifi analyses data from rifampicin time series created by microarray or RNAseq. rifi is a transcriptome data analysis tool for the holistic identification of transcription and decay associated processes. The decay constants and the delay of the onset of decay is fitted for each probe/bin. Subsequently, probes/bins of equal properties are combined into segments by dynamic programming, independent of a existing genome annotation. This allows to detect transcript segments of different stability or transcriptional events within one annotated gene. In addition to the classic decay constant/half-life analysis, rifi detects processing sites, transcription pausing sites, internal transcription start sites in operons, sites of partial transcription termination in operons, identifies areas of likely transcriptional interference by the collision mechanism and gives an estimate of the transcription velocity. All data are integrated to give an estimate of continous transcriptional units, i.e. operons. Comprehensive output tables and visualizations of the full genome result and the individual fits for all probes/bins are produced.

This package provides functionality for reading data from HDF Scalable Data Service from within R. The HSDSArray function bridges from HSDS to the user via the DelayedArray interface. Bioconductor manages an open HSDS instance graciously provided by John Readey of the HDF Group.

Automatically generated RnBeads annotation package for the assembly rn5.

This package is a pipeline to identify the key gene regulators in a biological process, for example in cell differentiation and in cell development after stimulation. There are four major steps in this pipeline: (1) differential expression analysis; (2) regulator-target network inference; (3) enrichment analysis; and (4) regulators scoring and ranking.

Microarray Classification is designed for both biologists and statisticians. It offers the ability to train a classifier on a labelled microarray dataset and to then use that classifier to predict the class of new observations. A range of modern classifiers are available, including support vector machines (SVMs), nearest shrunken centroids (NSCs)... Advanced methods are provided to estimate the predictive error rate and to report the subset of genes which appear essential in discriminating between classes.

Probabilistic analysis of probe reliability and differential gene expression on short oligonucleotide arrays.

Affymetrix Affymetrix RN_U34 Array annotation data (chip rnu34) assembled using data from public repositories.

Package provides clinical datasets from The Cancer Genome Atlas Project for all cohorts types from http://gdac.broadinstitute.org/. Clinical data format is explained here https://wiki.nci.nih.gov/display/TCGA/Clinical+Data+Overview. Data from 2015-11-01 snapshot.

Based on external numerous data files where rfPred scores are pre-calculated on all genomic positions of the human exome, the package gives rfPred scores to missense variants identified by the chromosome, the position (hg19 version), the referent and alternative nucleotids and the uniprot identifier of the protein. Note that for using the package, the user has to download the TabixFile and index (approximately 3.3 Go).

The Common Workflow Language (CWL) is an open standard for development of data analysis workflows that is portable and scalable across different tools and working environments. Rcwl provides a simple way to wrap command line tools and build CWL data analysis pipelines programmatically within R. It increases the ease of usage, development, and maintenance of CWL pipelines.

Agilent "Rat Genome, Whole" annotation data (chip rgug4131a) assembled using data from public repositories.

Microarray gene expression data from the study of Vawter et al., 2004.

Combine ideas of log-linear analysis of contingency table, flexible response function estimation and empirical Bayes dispersion estimation for explorative visualization of microbiome datasets. The package includes unconstrained as well as constrained analysis. In addition, diagnostic plot to detect lack of fit are available.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was RaGene-1\_0-st-v1\_probe\_tab.

This package provides a molecular informatics toolkit with an integration of bioinformatics and chemoinformatics tools for drug discovery.

Codelink Rat Inflammation 16 Bioarray annotation data (chip ri16cod) assembled using data from public repositories.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was Rice\_probe\_tab.

The ribor package provides an R Interface for .ribo files. It provides functionality to read the .ribo file, which is of HDF5 format, and performs common analyses on its contents.

Several quantitative and visualized benchmarks for RNA-seq quantification pipelines. Two-condition quantifications for genes, transcripts, junctions or exons by each pipeline with necessary meta information should be organized into numeric matrices in order to proceed the evaluation.

The rmspc package runs MSPC (Multiple Sample Peak Calling) software using R. The analysis of ChIP-seq samples outputs a number of enriched regions (commonly known as "peaks"), each indicating a protein-DNA interaction or a specific chromatin modification. When replicate samples are analyzed, overlapping peaks are expected. This repeated evidence can therefore be used to locally lower the minimum significance required to accept a peak. MSPC uses combined evidence from replicated experiments to evaluate peak calling output, rescuing peaks, and reduce false positives. It takes any number of replicates as input and improves sensitivity and specificity of peak calling on each, and identifies consensus regions between the input samples.

This package implements a variety of functions useful for gene set analysis using rotations to approximate the null distribution. It contributes with the implementation of seven test statistic scores that can be used with different goals and interpretations. Several functions are available to complement the statistical results with graphical representations.

An R package which interfaces the OME Bio-Formats Java library to allow reading of proprietary microscopy image data and metadata.