This package can be used to test two sets of gene lists and visualize the results.

This package provides a pure data-driven gene network, WGCN(weighted gene co-expression network) could be constructed only from expression profile. Different layers in such networks may represent different time points, multiple conditions or various species. AMOUNTAIN aims to search active modules in multi-layer WGCN using a continuous optimization approach.

The Triform algorithm uses model-free statistics to identify peak-like distributions of TF ChIP sequencing reads, taking advantage of an improved peak definition in combination with known profile characteristics.

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 provides a package containing an environment representing the HG_U95Av2.CDF file.

This package implements widgets to provide user interfaces.

RnBeads facilitates comprehensive analysis of various types of DNA methylation data at the genome scale.

Logistic Factor Analysis (LFA) is a method for a PCA analogue on Binomial data via estimation of latent structure in the natural parameter.

This package provides a number of utility functions for handling single-cell RNA-seq data from droplet technologies such as 10X Genomics. This includes data loading from count matrices or molecule information files, identification of cells from empty droplets, removal of barcode-swapped pseudo-cells, and downsampling of the count matrix.

This package defines low-level functions for mass spectrometry data and is independent of any high-level data structures. These functions include mass spectra processing functions (noise estimation, smoothing, binning), quantitative aggregation functions (median polish, robust summarisation, etc.), missing data imputation, data normalisation (quantiles, vsn, etc.) as well as misc helper functions, that are used across high-level data structure within the R for Mass Spectrometry packages.

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

This package provides an R wrapper of the popular bowtie2 sequencing reads aligner and AdapterRemoval, a convenient tool for rapid adapter trimming, identification, and read merging.

This package implements exact and approximate methods for singular value decomposition and principal components analysis, in a framework that allows them to be easily switched within Bioconductor packages or workflows. Where possible, parallelization is achieved using the BiocParallel framework.

This package provides an interface to implementations of the GatingML2.0 standard to exchange gated cytometry data with other software platforms.

Human Phenotype Ontology (HPO) was developed to create a consistent description of gene products with disease perspectives, and is essential for supporting functional genomics in disease context. Accurate disease descriptions can discover new relationships between genes and disease, and new functions for previous uncharacteried genes and alleles.

This package provides S4 generic functions needed by many Bioconductor packages.

This package provides tools to detect Gene Ontology and/or other user defined categories which are over/under represented in RNA-seq data.

This is a package for the automated analysis of Affymetrix arrays. It provides reporting features.

The project is intended to support the use of sequins(synthetic sequencing spike-in controls) owned and made available by the Garvan Institute of Medical Research. The goal is to provide a standard library for quantitative analysis, modelling, and visualization of spike-in controls.

This package provides a suite of methods for powerful and robust microbiome data analysis addressing zero-inflation, phylogenetic structure and compositional effects. The methods can be applied to the analysis of other (high-dimensional) compositional data arising from sequencing experiments.

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 provides classes for storing very large GWAS data sets and annotation, and functions for GWAS data cleaning and analysis.

The BADER package is intended for the analysis of RNA sequencing data. The algorithm fits a Bayesian hierarchical model for RNA sequencing count data. BADER returns the posterior probability of differential expression for each gene between two groups A and B. The joint posterior distribution of the variables in the model can be returned in the form of posterior samples, which can be used for further down-stream analyses such as gene set enrichment.

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