This package provides RcisTarget databases: Gene-based motif rankings and annotation to transcription factors. This package contains a subset of 4.6k motifs (cisbp motifs), scored only within 500bp upstream and the TSS. See RcisTarget tutorial to download the full databases, containing 20k motifs and search space up to 10kbp around the TSS.

The polyester package simulates RNA-seq reads from differential expression experiments with replicates. The reads can then be aligned and used to perform comparisons of methods for differential expression.

This package offers functionality for taking methtuple or Bismark outputs to calculate ASM scores and compute DAMEs regions. It also offers nice visualization of methyl-circle plots.

The Triform algorithm uses model-free statistics to identify peak-like distributions of TF ChIP sequencing reads, taking advantage of an improved peak definition in combination with known profile characteristics.

RnBeads facilitates comprehensive analysis of various types of DNA methylation data at the genome scale.

Saves the delayed operations of a DelayedArray to a HDF5 file. This enables efficient recovery of the DelayedArray's contents in other languages and analysis frameworks.

This package provides tools to produce a graphical display, as a heat map, of measures of pairwise linkage disequilibria between SNPs. Users may optionally include the physical locations or genetic map distances of each SNP on the plot.

The tRNA package allows tRNA sequences and structures to be accessed and used for subsetting. In addition, it provides visualization tools to compare feature parameters of multiple tRNA sets and correlate them to additional data. The tRNA package uses GRanges objects as inputs requiring only few additional column data sets.

This package provides functions that are needed by many other packages on Bioconductor or which replace R functions.

MultiBaC is a strategy to correct batch effects from multiomic datasets distributed across different labs or data acquisition events. MultiBaC is able to remove batch effects across different omics generated within separate batches provided that at least one common omic data type is included in all the batches considered.

This package contains functions and classes that are needed by arrayCGH packages.

This package ADAMgui is a graphical user interface (GUI) for the ADAM package. The ADAMgui package provides two shiny-based applications that allows the user to study the output of the ADAM package files through different plots. It's possible, for example, to choose a specific group of functionally associated genes (GFAG) and observe the gene expression behavior with the plots created with the GFAGtargetUi function. Features such as differential expression and fold change can be easily seen with aid of the plots made with the GFAGpathUi function.

Fit-Hi-C is a tool for assigning statistical confidence estimates to intra-chromosomal contact maps produced by genome-wide genome architecture assays such as Hi-C.

This package models a RESTful service as if it were a nested R list.

This package facilitates phyloseq exploration and analysis of taxonomic profiling data. This package provides tools for the manipulation, statistical analysis, and visualization of taxonomic profiling data. In addition to targeted case-control studies, microbiome facilitates scalable exploration of population cohorts. This package supports the independent phyloseq data format and expands the available toolkit in order to facilitate the standardization of the analyses and the development of best practices.

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 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.

The standard index of DNA methylation (beta) is computed from methylated and unmethylated signal intensities. Betas calculated from raw signal intensities perform well, but using 11 methylomic datasets we demonstrate that quantile normalization methods produce marked improvement. The commonly used procedure of normalizing betas is inferior to the separate normalization of M and U, and it is also advantageous to normalize Type I and Type II assays separately. This package provides 15 flavours of betas and three performance metrics, with methods for objects produced by the methylumi and minfi packages.

Starting with a BAM file, this package provides the necessary functions for quality assessment, read start position recalibration, the counting of genomic sequence reads on CDS, 3'UTR, and 5'UTR, and plotting of count data: pairs, log fold-change, codon frequency and coverage assessment, principal component analysis on codon coverage.

DSS is an R library performing differential analysis for count-based sequencing data. It detects differentially expressed genes (DEGs) from RNA-seq, and differentially methylated loci or regions (DML/DMRs) from bisulfite sequencing (BS-seq). The core of DSS is a dispersion shrinkage method for estimating the dispersion parameter from Gamma-Poisson or Beta-Binomial distributions.

In this package, a Hidden Semi Markov Model (HSMM) and one homogeneous segmentation model are designed and implemented for segmentation genomic data, with the aim of assisting in transcripts detection using high throughput technology like RNA-seq or tiling array, and copy number analysis using aCGH or sequencing.

This package identifies differential expression in high-throughput count data, such as that derived from next-generation sequencing machines, calculating estimated posterior likelihoods of differential expression (or more complex hypotheses) via empirical Bayesian methods.

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).

EBImage provides general purpose functionality for image processing and analysis. In the context of (high-throughput) microscopy-based cellular assays, EBImage offers tools to segment cells and extract quantitative cellular descriptors. This allows the automation of such tasks using the R programming language and facilitates the use of other tools in the R environment for signal processing, statistical modeling, machine learning and visualization with image data.