This package provides a software suite for the automated analysis of Affymetrix arrays.

This is an R package for doublet annotation of single cell RNA sequencing data. scds provides methods to annotate doublets in scRNA-seq data computationally.

This package is a visualization and analysis toolbox for short time course data which includes dimensionality reduction, clustering, two-sample differential expression testing and gene ranking techniques. The package also provides methods for retrieving enriched pathways.

This package implements the mini-batch k-means algorithm for large datasets, including support for on-disk data representation.

GOfuncR performs a gene ontology enrichment analysis based on the ontology enrichment software FUNC. GO-annotations are obtained from OrganismDb or OrgDb packages (Homo.sapiens by default); the GO-graph is included in the package and updated regularly. GOfuncR provides the standard candidate vs background enrichment analysis using the hypergeometric test, as well as three additional tests:

1. the Wilcoxon rank-sum test that is used when genes are ranked,

2. a binomial test that is used when genes are associated with two counts, and

3. a Chi-square or Fisher's exact test that is used in cases when genes are associated with four counts.

To correct for multiple testing and interdependency of the tests, family-wise error rates are computed based on random permutations of the gene-associated variables. GOfuncR also provides tools for exploring the ontology graph and the annotations, and options to take gene-length or spatial clustering of genes into account. It is also possible to provide custom gene coordinates, annotations and ontologies.

This package offers a statistical framework based on customizable permutation tests to assess the association between genomic region sets and other genomic features.

This package provides tools for exporting and importing classification trees and clusters to other programs.

This package provides processed 22 samples from BrainSpan keeping only the information for chromosome 21. Data is stored in the BigWig format and is used for examples in other packages.

biomaRt provides an interface to a growing collection of databases implementing the http://www.biomart.org. The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and dbSNP mapped to Ensembl. These major databases give biomaRt users direct access to a diverse set of data and enable a wide range of powerful online queries from gene annotation to database mining.

This is a package that can be used for quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets.

This package provides tools to create and plot diffusion maps.

SCONE is an R package for comparing and ranking the performance of different normalization schemes for single-cell RNA-seq and other high-throughput analyses.

This package AMARETTO represents an algorithm that integrates copy number, DNA methylation and gene expression data to identify a set of driver genes by analyzing cancer samples and connects them to clusters of co-expressed genes, which we define as modules. AMARETTO can be applied in a pancancer setting to identify cancer driver genes and their modules on multiple cancer sites. AMARETTO captures modules enriched in angiogenesis, cell cycle and EMT, and modules that accurately predict survival and molecular subtypes. This allows AMARETTO to identify novel cancer driver genes directing canonical cancer pathways.

Lefser is an implementation in R of the popular "LDA Effect Size" (LEfSe) method for microbiome biomarker discovery. It uses the Kruskal-Wallis test, Wilcoxon-Rank Sum test, and Linear Discriminant Analysis to find biomarkers of groups and sub-groups.

This is an annotation package for Illumina's EPIC methylation arrays.

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.

This package provides a collection of functions designed for analyzing deconvolution of the bulk sample(s) using an atlas of reference omic signature profiles and a user-selected model. Users are given the option to create or extend a reference atlas and,also simulate the desired size of the bulk signature profile of the reference cell types. The package includes the cell-type-specific methylation atlas and, Illumina Epic B5 probe ids that can be used in deconvolution. Additionally, we included BSmeth2Probe, to make mapping WGBS data to their probe IDs easier.

The MassSpecWavelet package aims to process Mass Spectrometry (MS) data mainly through the use of wavelet transforms. It supports peak detection based on Continuous Wavelet Transform (CWT).

This package provides efficient low-level and highly reusable S4 classes for storing ranges of integers, RLE vectors (Run-Length Encoding), and, more generally, data that can be organized sequentially (formally defined as Vector objects), as well as views on these Vector objects. Efficient list-like classes are also provided for storing big collections of instances of the basic classes. All classes in the package use consistent naming and share the same rich and consistent "Vector API" as much as possible.

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

This is a package for saving Bioconductor data structures into file artifacts, and loading them back into memory. This is a more robust and portable alternative to serialization of such objects into RDS files. Each artifact is associated with metadata for further interpretation; downstream applications can enrich this metadata with context-specific properties.

This package implements the density-preserving modification to t-SNE and UMAP described by Narayan et al. (2020) <doi:10.1101/2020.05.12.077776>. den-SNE and densMAP aim to enable more accurate visual interpretation of high-dimensional datasets by producing lower-dimensional embeddings that accurately represent the heterogeneity of the original high-dimensional space, enabling the identification of homogeneous and heterogeneous cell states. This accuracy is accomplished by including in the optimisation process a term which considers the local density of points in the original high-dimensional space. This can help to create visualisations that are more representative of heterogeneity in the original high-dimensional space.

This package provides a collection of software tools for calculating distance measures.

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