The package provides utility functions related to package development. These include functions that replace slots, and selectors for show methods. It aims to coalesce the various helper functions often re-used throughout the Bioconductor ecosystem.

Animalcules is an R package for utilizing up-to-date data analytics, visualization methods, and machine learning models to provide users an easy-to-use interactive microbiome analysis framework. It can be used as a standalone software package or users can explore their data with the accompanying interactive R Shiny application. Traditional microbiome analysis such as alpha/beta diversity and differential abundance analysis are enhanced, while new methods like biomarker identification are introduced by animalcules. Powerful interactive and dynamic figures generated by animalcules enable users to understand their data better and discover new insights.

EpiDISH is a R package to infer the proportions of a priori known cell-types present in a sample representing a mixture of such cell-types. Right now, the package can be used on DNAm data of whole blood, generic epithelial tissue and breast tissue. Besides, the package provides a function that allows the identification of differentially methylated cell-types and their directionality of change in Epigenome-Wide Association Studies.

The rpx package implements an interface to proteomics data submitted to the ProteomeXchange consortium.

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.

Feature selection is critical in omics data analysis to extract restricted and meaningful molecular signatures from complex and high-dimension data, and to build robust classifiers. This package implements a method to assess the relevance of the variables for the prediction performances of the classifier. The approach can be run in parallel with the PLS-DA, Random Forest, and SVM binary classifiers. The signatures and the corresponding 'restricted' models are returned, enabling future predictions on new datasets.

This package provides tools for differential expression biomarker discovery based on microarray and next-generation sequencing data that leverage efficient semiparametric estimators of the average treatment effect for variable importance analysis. Estimation and inference of the (marginal) average treatment effects of potential biomarkers are computed by targeted minimum loss-based estimation, with joint, stable inference constructed across all biomarkers using a generalization of moderated statistics for use with the estimated efficient influence function. The procedure accommodates the use of ensemble machine learning for the estimation of nuisance functions.

This package provides a package for the annotation and gene expression data download from Bgee database, and TopAnat analysis: GO-like enrichment of anatomical terms, mapped to genes by expression patterns.

This is a package to support identification of markers of rare cell types by looking at genes whose expression is confined in small regions of the expression space.

This package provides a set of tools to for machine and deep learning in R from amino acid and nucleotide sequences focusing on adaptive immune receptors. The package includes pre-processing of sequences, unifying gene nomenclature usage, encoding sequences, and combining models. This package will serve as the basis of future immune receptor sequence functions/packages/models compatible with the scRepertoire ecosystem.

This package provides functions for the integrated analysis of protein-protein interaction networks and the detection of functional modules. Different datasets can be integrated into the network by assigning p-values of statistical tests to the nodes of the network. E.g. p-values obtained from the differential expression of the genes from an Affymetrix array are assigned to the nodes of the network. By fitting a beta-uniform mixture model and calculating scores from the p-values, overall scores of network regions can be calculated and an integer linear programming algorithm identifies the maximum scoring subnetwork.

This package creates a persistent on-disk cache of files that the user can add, update, and retrieve. It is useful for managing resources (such as custom Txdb objects) that are costly or difficult to create, web resources, and data files used across sessions.

This package provides a package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).

INSPEcT (INference of Synthesis, Processing and dEgradation rates in Time-Course experiments) analyses 4sU-seq and RNA-seq time-course data in order to evaluate synthesis, processing and degradation rates and assess via modeling the rates that determines changes in mature mRNA levels.

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.

This package provides methods and functionality to analyze flow data that is beyond the basic infrastructure provided by the flowCore package.

This package speeds up the derfinder package when using multiple cores. It is particularly useful when using BiocParallel and it helps reduce the time spent loading the full derfinder package when running the F-statistics calculation in parallel.

The affyPLM provides a package that extends and improves the functionality of the base affy package. For speeding up the runs, it includes routines that make heavy use of compiled code. The central focus is on implementation of methods for fitting probe-level models and tools using these models. PLM based quality assessment tools are also provided.

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

ChemmineOB provides an R interface to a subset of cheminformatics functionalities implemented by the OpelBabel C++ project. OpenBabel is a free cheminformatics toolbox that includes utilities for structure format interconversions, descriptor calculations, compound similarity searching and more. ChemineOB aims to make a subset of these utilities available from within R. For non-developers, ChemineOB is primarily intended to be used from ChemmineR as an add-on package rather than used directly.

This package includes positive ionization mode data in NetCDF file format. Centroided subset from 200-600 m/z and 2500-4500 seconds. Data originally reported in "Assignment of Endogenous Substrates to Enzymes by Global Metabolite Profiling" Biochemistry; 2004; 43(45). It also includes detected peaks in an xcmsSet.

DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It models the expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles.

The genome is divided into non-overlapping fixed-sized bins, number of sequence reads in each counted, adjusted with a simultaneous two-dimensional loess correction for sequence mappability and GC content, and filtered to remove spurious regions in the genome. Downstream steps of segmentation and calling are also implemented via packages DNAcopy and CGHcall, respectively.

This package provides full genome sequences for Homo sapiens (Human) as provided by UCSC (hg19, Feb. 2009) and stored in Biostrings objects. The sequences are the same as in BSgenome.Hsapiens.UCSC.hg19, 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), and (4) the mask of repeats from Tandem Repeats Finder (TRF mask). Only the AGAPS and AMB masks are "active" by default.