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This package provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.
This package provides R functions for common pre-processing steps that are applied on 1H-NMR data. It also provides a function to read the FID signals directly in the Bruker format.
R-escape streamlines gene set enrichment analysis for single-cell RNA sequencing. Using raw count information, Seurat objects, or SingleCellExperiment format, users can perform and visualize GSEA across individual cells.
This package provides a pipeline for the analysis of GRO-seq data.
This package is to find SNV/Indel differences between two bam files with near relationship in a way of pairwise comparison through each base position across the genome region of interest. The difference is inferred by Fisher test and euclidean distance, the input of which is the base count (A,T,G,C) in a given position and read counts for indels that span no less than 2bp on both sides of indel region.
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 set of tools for interacting with GO and microarray data. A variety of basic manipulation tools for graphs, hypothesis testing and other simple calculations.
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 is an annotation package for Illumina's EPIC methylation arrays.
This package implements algorithms for calculating microarray enrichment (ACME), and it is a set of tools for analysing tiling array of combined chromatin immunoprecipitation with DNA microarray (ChIP/chip), DNAse hypersensitivity, or other experiments that result in regions of the genome showing enrichment. It does not rely on a specific array technology (although the array should be a tiling array), is very general (can be applied in experiments resulting in regions of enrichment), and is very insensitive to array noise or normalization methods. It is also very fast and can be applied on whole-genome tiling array experiments quite easily with enough memory.
This package provides methods for working with Illumina arrays using the gdsfmt package.
This package extends the ggplot2 plotting system which implements a grammar of graphics. ggtree is designed for visualization and annotation of phylogenetic trees and other tree-like structures with their annotation data.
ASEB is an R package to predict lysine sites that can be acetylated by a specific KAT (K-acetyl-transferases) family. Lysine acetylation is a well-studied posttranslational modification on kinds of proteins. About four thousand lysine acetylation sites and over 20 lysine KATs have been identified. However, which KAT is responsible for a given protein or lysine site acetylation is mostly unknown. In this package, we use a GSEA-like (Gene Set Enrichment Analysis) method to make predictions. GSEA method was developed and successfully used to detect coordinated expression changes and find the putative functions of the long non-coding RNAs.
r-circrnaprofiler is a computational framework for a comprehensive in silico analysis of circular RNA (circRNAs). This computational framework allows combining and analyzing circRNAs previously detected by multiple publicly available annotation-based circRNA detection tools. It covers different aspects of circRNAs analysis from differential expression analysis, evolutionary conservation, biogenesis to functional analysis.
This is an R package for interfacing with the BIOM format. This package includes basic tools for reading biom-format files, accessing and subsetting data tables from a biom object (which is more complex than a single table), as well as limited support for writing a biom-object back to a biom-format file. The design of this API is intended to match the Python API and other tools included with the biom-format project, but with a decidedly "R flavor" that should be familiar to R users. This includes S4 classes and methods, as well as extensions of common core functions/methods.
This package contains a SummarizedExperiment from the Yu et al. (2013) paper that performed the rat BodyMap across 11 organs and 4 developmental stages. Raw FASTQ files were downloaded and mapped using STAR. Data is available on ExperimentHub as a data package.
This package provides plotting functions, frameshift detection and parsing of genetic sequencing data from ribosome profiling experiments.
This package provides a consistent C++ class interface for a variety of commonly used matrix types, including sparse and HDF5-backed matrices.
The ggbio package extends and specializes the grammar of graphics for biological data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.
This package provides tools to identify cell populations in Flow Cytometry data using non-parametric clustering and segmented-regression-based change point detection.
The package provides functions to create and use transcript-centric annotation databases/packages. The annotation for the databases are directly fetched from Ensembl using their Perl API. The functionality and data is similar to that of the TxDb packages from the GenomicFeatures package, but, in addition to retrieve all gene/transcript models and annotations from the database, the ensembldb package also provides a filter framework allowing to retrieve annotations for specific entries like genes encoded on a chromosome region or transcript models of lincRNA genes.
ATAC-seq, an assay for Transposase-Accessible Chromatin using sequencing, is a rapid and sensitive method for chromatin accessibility analysis. It was developed as an alternative method to MNase-seq, FAIRE-seq and DNAse-seq. The ATACseqQC package was developed to help users to quickly assess whether their ATAC-seq experiment is successful. It includes diagnostic plots of fragment size distribution, proportion of mitochondria reads, nucleosome positioning pattern, and CTCF or other Transcript Factor footprints.
This package provides basic plotting, data manipulation and processing of mass spectrometry based proteomics data.
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.