This package provides tools for differential expression analysis at both gene and isoform level using RNA-seq data

This package stores the data employed in the vignette of the GSVA package. These data belong to the following publications: Armstrong et al. Nat Genet 30:41-47, 2002; Cahoy et al. J Neurosci 28:264-278, 2008; Carrel and Willard, Nature, 434:400-404, 2005; Huang et al. PNAS, 104:9758-9763, 2007; Pickrell et al. Nature, 464:768-722, 2010; Skaletsky et al. Nature, 423:825-837; Verhaak et al. Cancer Cell 17:98-110, 2010; Costa et al. FEBS J, 288:2311-2331, 2021.

This package expands the usethis package with the goal of helping automate the process of creating R packages for Bioconductor or making them Bioconductor-friendly.

This package contains functions and classes that are needed by arrayCGH packages.

This package provides functions for calculation and visualization of performance metrics for evaluation of ranking and binary classification (assignment) methods. It also contains a Shiny application for interactive exploration of results.

This package provides a computational method that infers copy number variations (CNV) in cancer scRNA-seq data and reconstructs the tumor phylogeny. It integrates signals from gene expression, allelic ratio, and population haplotype structures to accurately infer allele-specific CNVs in single cells and reconstruct their lineage relationship. It does not require tumor/normal-paired DNA or genotype data, but operates solely on the donor scRNA-data data (for example, 10x Cell Ranger output). It can be used to:

1. detect allele-specific copy number variations from single-cells

2. differentiate tumor versus normal cells in the tumor microenvironment

3. infer the clonal architecture and evolutionary history of profiled tumors

For details on the method see Gao et al in Nature Biotechnology 2022.

This package contains functions for the efficient design of factorial two-colour microarray experiments and for the statistical analysis of factorial microarray data.

This package provides an R wrapper around the popular bowtie short read aligner and around SpliceMap, a de novo splice junction discovery and alignment tool.

The package ANF(Affinity Network Fusion) provides methods for affinity matrix construction and fusion as well as spectral clustering. This package is used for complex patient clustering by integrating multi-omic data through affinity network fusion.

Exploratory data analysis to assess the quality of a set of LC-MS/MS experiments, and visualize de influence of the involved factors.

This package defines an S4 class for storing data from single-cell experiments. This includes specialized methods to store and retrieve spike-in information, dimensionality reduction coordinates and size factors for each cell, along with the usual metadata for genes and libraries.

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

This package provides an expressionSet containing gene expression data from 60 bone marrow samples of patients with one of the four main types of leukemia (ALL, AML, CLL, CML) or non-leukemia.

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.

This package provides methods for microarray analysis that take basic data types such as matrices and lists of vectors. These methods can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes.

This package provides a pipeline for analysing Capture Hi-C data.

This package provides functions to detect and correct for batch effects in DNA methylation data. The core function is based on latent factor models and can also be used to predict missing values in any other matrix containing real numbers.

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.

The purpose of this package is to simplify the storage and interrogation of quantitative trait loci (QTL) archives, such as eQTL, mQTL, dsQTL, and more.

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

This package provides a client for the OmniPath web service and many other resources. It also includes functions to transform and pretty print some of the downloaded data, functions to access a number of other resources. Furthermore, OmnipathR features a close integration with the NicheNet method for ligand activity prediction from transcriptomics data.

The ASAFE package contains a collection of functions that can be used to carry out an EM (Expectation–maximization) algorithm to estimate ancestry-specific allele frequencies for a bi-allelic genetic marker, e.g. an SNP (single nucleotide polymorphism) from genotypes and ancestry pairs.

This package provides functions and classes for de novo prediction of transcription factor binding consensus by heuristic search.

This package provides full genome sequences for Mus musculus (Mouse) as provided by UCSC (mm10, December 2011) and stored in Biostrings objects.