This package provides an implementation of an algorithm for recalibrating the base quality scores for aligned sequencing data in BAM format.

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.

The purpose of biocViews is to create HTML pages that categorize packages in a Bioconductor package repository according to keywords, also known as views, in a controlled vocabulary.

This package provides S4 data structures and basic functions to deal with flow cytometry data.

This package provides full genome sequences for Homo sapiens from 1000genomes phase2 reference genome sequence (hs37d5), based on NCBI GRCh37.

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 provides tools for parsing Illumina's microarray output files, including IDAT.

This package provides the output of running Salmon on a set of 24 RNA-seq samples from Alasoo, et al. "Shared genetic effects on chromatin and gene expression indicate a role for enhancer priming in immune response", published in Nature Genetics, January 2018.

The global test tests groups of covariates (or features) for association with a response variable. This package implements the test with diagnostic plots and multiple testing utilities, along with several functions to facilitate the use of this test for gene set testing of GO and KEGG terms.

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.

This package provides full genome sequences for Mus musculus (Mouse) as provided by UCSC (mm9, July 2007) and stored in Biostrings objects.

This package provides S4 generic functions modeled after the matrixStats API for alternative matrix implementations. Packages with alternative matrix implementation can depend on this package and implement the generic functions that are defined here for a useful set of row and column summary statistics. Other package developers can import this package and handle a different matrix implementations without worrying about incompatibilities.

The sparse nature of single cell epigenomics data can be overruled using probabilistic modelling methods such as Latent Dirichlet Allocation (LDA). This package allows the probabilistic modelling of cis-regulatory topics (cisTopics) from single cell epigenomics data, and includes functionalities to identify cell states based on the contribution of cisTopics and explore the nature and regulatory proteins driving them.

This package provides publicly available data from The Cancer Genome Atlas (TCGA) as MultiAssayExperiment objects. MultiAssayExperiment integrates multiple assays (e.g., RNA-seq, copy number, mutation, microRNA, protein, and others) with clinical / pathological data. It also links assay barcodes with patient identifiers, enabling harmonized subsetting of rows (features) and columns (patients / samples) across the entire multi-'omics experiment.

This package ofers functions for importation, normalization, visualization, and quality control to correct identified sources of variability in array of CGH experiments.

This package contains data and functions that define and allow translation between different chromosome sequence naming conventions (e.g., "chr1" versus "1"), including a function that attempts to place sequence names in their natural, rather than lexicographic, order.

This package implements different performance measures for classification and ranking tasks. Area under curve (AUC), precision at a given recall, F-score for single and multiple classes are available.

This package implements a general and flexible zero-inflated negative binomial model that can be used to provide a low-dimensional representations of single-cell RNA-seq data. The model accounts for zero inflation (dropouts), over-dispersion, and the count nature of the data. The model also accounts for the difference in library sizes and optionally for batch effects and/or other covariates, avoiding the need for pre-normalize the data.

This package provides more than 2000 annotated position frequency matrices from nine public sources, for multiple organisms.

This package provides a quality control pipeline for ChIP-exo/nexus sequencing data.

This package is an R program for the subset-based analysis of heterogeneous traits and disease subtypes. ASSET allows the user to search through all possible subsets of z-scores to identify the subset of traits giving the best meta-analyzed z-score. Further, it returns a p-value adjusting for the multiple-testing involved in the search. It also allows for searching for the best combination of disease subtypes associated with each variant.

This package provides classes and other infrastructure to implement filters for manipulating Bioconductor annotation resources. The filters are used by ensembldb, Organism.dplyr, and other packages.

This is a package for saving matrices, arrays and similar objects into file artifacts, and loading them back into memory. This is a more 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.

CelliD is a clustering-free method for extracting per-cell gene signatures from scRNA-seq. CelliD allows unbiased cell identity recognition across different donors, tissues-of-origin, model organisms and single-cell omics protocols. The package can also be used to explore functional pathways enrichment in single cell data.