This package provides an R interface to Illumina's BaseSpace cloud computing environment, enabling the fast development of data analysis and visualization tools. Besides providing an easy to use set of tools for manipulating the data from BaseSpace, it also facilitates the access to R's rich environment of statistical and data analysis tools.

The NCBI Gene Expression Omnibus (GEO) is a public repository of microarray data. Given the rich and varied nature of this resource, it is only natural to want to apply BioConductor tools to these data. GEOquery is the bridge between GEO and BioConductor.

The airpart package identifies sets of genes displaying differential cell-type-specific allelic imbalance across cell types or states, utilizing single-cell allelic counts. It makes use of a generalized fused lasso with binomial observations of allelic counts to partition cell types by their allelic imbalance. Alternatively, a nonparametric method for partitioning cell types is offered. The package includes a number of visualizations and quality control functions for examining single cell allelic imbalance datasets.

This package provides an interactive tool for visualizing Illumina methylation array data. Both the 450k and EPIC array are supported.

Expression levels of mRNA molecules are regulated by different processes, comprising inhibition or activation by transcription factors and post-transcriptional degradation by microRNAs. birta (Bayesian Inference of Regulation of Transcriptional Activity) uses the regulatory networks of transcription factors and miRNAs together with mRNA and miRNA expression data to predict switches in regulatory activity between two conditions. A Bayesian network is used to model the regulatory structure and Markov-Chain-Monte-Carlo is applied to sample the activity states.

R-escape streamlines gene set enrichment analysis for single-cell RNA sequencing. Using raw count information, Seurat objects, or SingleCellExperiment format, users can perform and visualize GSEA across individual cells.

The package contains 8 BAM files, 1 per sequencing run. Each BAM file was obtained by aligning the reads (paired-end) to the full hg19 genome with TopHat2, and then subsetting to keep only alignments on chr14. See accession number E-MTAB-1147 in the ArrayExpress database for details about the experiment, including links to the published study (by Zarnack et al., 2012) and to the FASTQ files.

This package provides a library of core pre-processing and normalization routines.

This package provides tools to display a rectangular heatmap (intensity plot) of a data matrix. By default, both samples (columns) and features (row) of the matrix are sorted according to a hierarchical clustering, and the corresponding dendrogram is plotted. Optionally, panels with additional information about samples and features can be added to the plot.

This package provides a parser for mzIdentML files implemented using the XML package. The parser tries to be general and able to handle all types of mzIdentML files with the drawback of having less pretty output than a vendor specific parser.

The package uses quadratic programming for signature refitting, i.e., to decompose the mutation catalog from an individual tumor sample into a set of given mutational signatures (either Alexandrov-model signatures or Shiraishi-model signatures), computing weights that reflect the contributions of the signatures to the mutation load of the tumor.

This package allows importing most common specific structure (motif) types into R for use by functions provided by other Bioconductor motif-related packages. Motifs can be exported into most major motif formats from various classes as defined by other Bioconductor packages. A suite of motif and sequence manipulation and analysis functions are included, including enrichment, comparison, P-value calculation, shuffling, trimming, higher-order motifs, and others.

The AffiXcan package imputes a genetically regulated expression (GReX) for a set of genes in a sample of individuals, using a method based on the total binding affinity (TBA). Statistical models to impute GReX can be trained with a training dataset where the real total expression values are known.

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

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 functionalities for downstream analysis, annotation and visualizaton of alternative splicing events generated by rMATS.

This package provides basic plotting, data manipulation and processing of mass spectrometry based proteomics data.

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.

iClusterPlus is developed for integrative clustering analysis of multi-type genomic data and is an enhanced version of iCluster proposed and developed by Shen, Olshen and Ladanyi (2009). Multi-type genomic data arise from the experiments where biological samples (e.g. tumor samples) are analyzed by multiple techniques, for instance, array comparative genomic hybridization (aCGH), gene expression microarray, RNA-seq and DNA-seq, and so on. In the iClusterPlus model, binary observations such as somatic mutation are modeled as Binomial processes; categorical observations such as copy number states are realizations of Multinomial random variables; counts are modeled as Poisson random processes; and continuous measures are modeled by Gaussian distributions.

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

This package is importing data from Illumina SNP experiments and it performs copy number calculations and reports.

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

This package implements some simple capabilities for representing and manipulating hypergraphs.

This package uses a Bayesian hierarchical model to detect enriched regions from ChIP-chip experiments. The common goal in analyzing this ChIP-chip data is to detect DNA-protein interactions from ChIP-chip experiments. The BAC package has mainly been tested with Affymetrix tiling array data. However, we expect it to work with other platforms (e.g. Agilent, Nimblegen, cDNA, etc.). Note that BAC does not deal with normalization, so you will have to normalize your data beforehand.