This package offers functions to process multiple ChIP-seq BAM files and detect allele-specific events. It computes allele counts at individual variants (SNPs/SNVs), implements extensive QC (quality control) steps to remove problematic variants, and utilizes a Bayesian framework to identify statistically significant allele-specific events. BaalChIP is able to account for copy number differences between the two alleles, a known phenotypical feature of cancer samples.

This package takes a list of p-values resulting from the simultaneous testing of many hypotheses and estimates their q-values and local false discovery rate (FDR) values. The q-value of a test measures the proportion of false positives incurred when that particular test is called significant. The local FDR measures the posterior probability the null hypothesis is true given the test's p-value. Various plots are automatically generated, allowing one to make sensible significance cut-offs. The software can be applied to problems in genomics, brain imaging, astrophysics, and data mining.

Bacon can be used to remove inflation and bias often observed in epigenome- and transcriptome-wide association studies. To this end bacon constructs an empirical null distribution using a Gibbs Sampling algorithm by fitting a three-component normal mixture on z-scores.

This package is able to perform an automatic or interactive quality control on FCS data acquired using flow cytometry instruments. By evaluating three different properties:

1. flow rate

2. signal acquisition, and

3. dynamic range,

the quality control enables the detection and removal of anomalies.

The AnVIL is a cloud computing resource developed in part by the National Human Genome Research Institute. The AnVIL package provides end-user and developer functionality. AnVIL provides fast binary package installation, utilities for working with Terra/AnVIL table and data resources, and convenient functions for file movement to and from Google cloud storage. For developers, AnVIL provides programmatic access to the Terra, Leonardo, Rawls, Dockstore, and Gen3 RESTful programming interface, including helper functions to transform JSON responses to formats more amenable to manipulation in R.

The S4Arrays package defines the Array virtual class to be extended by other S4 classes that wish to implement a container with an array-like semantic. It also provides:

1. low-level functionality meant to help the developer of such container to implement basic operations like display, subsetting, or coercion of their array-like objects to an ordinary matrix or array, and

2. a framework that facilitates block processing of array-like objects (typically on-disk objects).

Wrench is a package for normalization sparse genomic count data, like that arising from 16s metagenomic surveys.

AbSeq is a comprehensive bioinformatic pipeline for the analysis of sequencing datasets generated from antibody libraries and abseqR is one of its packages. AbseqR empowers the users of abseqPy with plotting and reporting capabilities and allows them to generate interactive HTML reports for the convenience of viewing and sharing with other researchers. Additionally, abseqR extends abseqPy to compare multiple repertoire analyses and perform further downstream analysis on its output.

The epigenomics road map describes locations of epigenetic marks in DNA from a variety of cell types. Of interest are locations of histone modifications, sites of DNA methylation, and regions of accessible chromatin. This package presents a selection of elements of the road map including metadata and outputs of the ChromImpute procedure applied to ENCODE cell lines by Ernst and Kellis.

Store minor allele frequency data from the Phase 1 of the 1000 Genomes Project for the human genome version hs37d5.

This package provides tools to visualize oligonucleotide patterns and sequence motif occurrences across a large set of sequences centred at a common reference point and sorted by a user defined feature.

Phyloseq provides a set of classes and tools to facilitate the import, storage, analysis, and graphical display of microbiome census data.

This package provides an R interface to libsbml for SBML parsing, validating output, provides an S4 SBML DOM, converts SBML to R graph objects.

This package provides tools to acquire, annotate, convert and store data for use in Bioconductor’s AnnotationHub.

This is a package for the analysis of alternative splicing and isoform switches with predicted functional consequences (e.g. gain/loss of protein domains etc.) from quantification of all types of RNASeq by tools such as Kallisto, Salmon, StringTie, Cufflinks/Cuffdiff etc.

This package provides tools for large-scale identification and advanced visualization of sets of conserved noncoding elements.

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

This package provides functions for reading array comparative genomic hybridization (aCGH) data from image analysis output files and clone information files, creation of aCGH objects for storing these data. Basic methods are accessing/replacing, subsetting, printing and plotting aCGH objects.

This is the classification package for the automated analysis of Affymetrix arrays.

This package provides the complete genome sequences for Homo sapiens as provided by UCSC (genome hg38, based on assembly GRCh38.p14 since 2023/01/31). The sequences are the same as in BSgenome.Hsapiens.UCSC.hg38, except that each of them has the 4 following masks on top:

1. the mask of assembly gaps (AGAPS mask);

2. the mask of intra-contig ambiguities (AMB mask);

3. the mask of repeats from RepeatMasker (RM mask);

4. the mask of repeats from Tandem Repeats Finder (TRF mask).

Only the AGAPS and AMB masks are "active" by default. The sequences are stored in MaskedDNAString objects.

Linnorm is an R package for the analysis of RNA-seq, scRNA-seq, ChIP-seq count data or any large scale count data. It transforms such datasets for parametric tests. In addition to the transformtion function (Linnorm), the following pipelines are implemented:

1. Library size/batch effect normalization (Linnorm.Norm)

2. Cell subpopluation analysis and visualization using t-SNE or PCA K-means clustering or hierarchical clustering (Linnorm.tSNE, Linnorm.PCA, Linnorm.HClust)

3. Differential expression analysis or differential peak detection using limma (Linnorm.limma)

4. Highly variable gene discovery and visualization (Linnorm.HVar)

5. Gene correlation network analysis and visualization (Linnorm.Cor)

6. Stable gene selection for scRNA-seq data; for users without or who do not want to rely on spike-in genes (Linnorm.SGenes)

7. Data imputation (Linnorm.DataImput).

Linnorm can work with raw count, CPM, RPKM, FPKM and TPM. Additionally, the RnaXSim function is included for simulating RNA-seq data for the evaluation of DEG analysis methods.

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.

This package provides tools for the computationally efficient analysis of quantitative trait loci (QTL) data, including eQTL, mQTL, dsQTL, etc. The software in this package aims to support refinements and functional interpretation of members of a collection of association statistics on a family of feature/genome hypotheses.

This package offers the possibility to access the ArrayExpress repository at EBI (European Bioinformatics Institute) and build Bioconductor data structures: ExpressionSet, AffyBatch, NChannelSet.