This package provides functions for plotting genomic data.

This package provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.

This package provides a framework for allele-specific expression investigation using RNA-seq data.

The atena package quantifies expression of TEs (transposable elements) from RNA-seq data through different methods, including ERVmap, TEtranscripts and Telescope. A common interface is provided to use each of these methods, which consists of building a parameter object, calling the quantification function with this object and getting a SummarizedExperiment object as an output container of the quantified expression profiles. The implementation allows quantifing TEs and gene transcripts in an integrated manner.

FlowSOM offers visualization options for cytometry data, by using self-organizing map clustering and minimal spanning trees.

The package ABAEnrichment is designed to test for enrichment of user defined candidate genes in the set of expressed genes in different human brain regions. The core function aba_enrich integrates the expression of the candidate gene set (averaged across donors) and the structural information of the brain using an ontology, both provided by the Allen Brain Atlas project.

ANCOMBC is a package containing differential abundance (DA) and correlation analyses for microbiome data. Specifically, the package includes Analysis of Compositions of Microbiomes with Bias Correction(ANCOM-BC) and Analysis of Composition of Microbiomes (ANCOM) for DA analysis, and Sparse Estimation of Correlations among Microbiomes (SECOM) for correlation analysis. Microbiome data are typically subject to two sources of biases: unequal sampling fractions (sample-specific biases) and differential sequencing efficiencies (taxon-specific biases). Methodologies included in the ANCOMBC package were designed to correct these biases and construct statistically consistent estimators.

This package wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. Conos focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes.

This package analyzes and creates plots of array CGH data. Also, it allows usage of CBS, wavelet-based smoothing, HMM, BioHMM, GLAD, CGHseg. Most computations are parallelized (either via forking or with clusters, including MPI and sockets clusters) and use ff for storing data.

This package provides infrastructure to store and access genome-wide position-specific scores within R and Bioconductor.

TFBSTools is a package for the analysis and manipulation of transcription factor binding sites. It includes matrices conversion between Position Frequency Matrix (PFM), Position Weight Matrix (PWM) and Information Content Matrix (ICM). It can also scan putative TFBS from sequence/alignment, query JASPAR database and provides a wrapper of de novo motif discovery software.

This package offers tools to create DNA barcode sets capable of correcting insertion, deletion, and substitution errors. Existing barcodes can be analyzed regarding their minimal, maximal and average distances between barcodes. Finally, reads that start with a (possibly mutated) barcode can be demultiplexed, i.e. assigned to their original reference barcode.

This package provides high level functions for reading Affy .CEL files, phenotypic data, and then computing simple things with it, such as t-tests, fold changes and the like. It makes heavy use of the affy library. It also has some basic scatter plot functions and mechanisms for generating high resolution journal figures.

This package provides full genome sequences for Mus musculus (Mouse) as provided by UCSC (mm10, December 2011) and stored in Biostrings objects.

This package can do differential expression analysis of RNA-seq expression profiles with biological replication. It implements a range of statistical methodology based on the negative binomial distributions, including empirical Bayes estimation, exact tests, generalized linear models and quasi-likelihood tests. It be applied to differential signal analysis of other types of genomic data that produce counts, including ChIP-seq, SAGE and CAGE.

This package provides a function to impute missing gene expression microarray data, using nearest neighbor averaging.

The package provides two frameworks. One for the differential transcript usage analysis between different conditions and one for the tuQTL analysis. Both are based on modeling the counts of genomic features (i.e., transcripts) with the Dirichlet-multinomial distribution. The package also makes available functions for visualization and exploration of the data and results.

This package is an implementation of the Adaptively Weighted Fisher's method, including fast p-value computing, variability index, and meta-pattern.

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.

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 contains class definitions for two-color spotted microarray data. It also includes functions for data input, diagnostic plots, normalization and quality checking.

This package provides Ion Trap positive ionization mode data in mzML file format. It includes a subset from 500-850 m/z and 1190-1310 seconds, including MS2 and MS3, intensity threshold 100.000; extracts from FTICR Apex III, m/z 400-450; a subset of UPLC - Bruker micrOTOFq data, both mzML and mz5; LC-MSMS and MRM files from proteomics experiments; and PSI mzIdentML example files for various search engines.

This package is developed for the analysis and visualization of clonal tracking data. The required data is formed by samples and tag abundances in matrix form, usually from cellular barcoding experiments, integration site retrieval analyses, or similar technologies.

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