This package provides Escherichia coli full genomes for several strains as provided by NCBI on 2008/08/05 and stored in Biostrings objects.

The package is usable with Affymetrix GeneChip short oligonucleotide arrays, and it can be adapted or extended to other platforms. It is able to modify or replace the grouping of probes in the probe sets. Also, the package contains simple functions to read R connections in the FASTA format and it can create an alternative mapping from sequences.

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

DeconSeq is an R package for deconvolution of heterogeneous tissues based on mRNA-Seq data. It models the expression levels from heterogeneous cell populations in mRNA-Seq as the weighted average of expression from different constituting cell types and predicted cell type proportions of single expression profiles.

This package provides a set of annotation maps describing the entire Human Disease Ontology. The annotation data comes from https://github.com/DiseaseOntology/HumanDiseaseOntology/tree/main/src/ontology.

This package wires together large collections of single-cell RNA-seq datasets, which allows for both the identification of recurrent cell clusters and the propagation of information between datasets in multi-sample or atlas-scale collections. Conos focuses on the uniform mapping of homologous cell types across heterogeneous sample collections. For instance, users could investigate a collection of dozens of peripheral blood samples from cancer patients combined with dozens of controls, which perhaps includes samples of a related tissue such as lymph nodes.

This package provides tools to efficiently represent and manipulate genomic annotations and alignments is playing a central role when it comes to analyzing high-throughput sequencing data (a.k.a. NGS data). The GenomicRanges package defines general purpose containers for storing and manipulating genomic intervals and variables defined along a genome.

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.

Wrapping an array-like object (typically an on-disk object) in a DelayedArray object allows one to perform common array operations on it without loading the object in memory. In order to reduce memory usage and optimize performance, operations on the object are either delayed or executed using a block processing mechanism. Note that this also works on in-memory array-like objects like DataFrame objects (typically with Rle columns), Matrix objects, and ordinary arrays and data frames.

This package provides a manifest for Illumina's 450k array 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 provides tools for analysis of ChIP-seq and other functional sequencing data.

This package represents an integrative method of analyzing multi omics data that conducts enrichment analysis of annotated gene sets. ActivePathways uses a statistical data fusion approach, rationalizes contributing evidence and highlights associated genes, improving systems-level understanding of cellular organization in health and disease.

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 package provides a collection of functions for left-censored missing data imputation. Left-censoring is a special case of missing not at random (MNAR) mechanism that generates non-responses in proteomics experiments. The package also contains functions to artificially generate peptide/protein expression data (log-transformed) as random draws from a multivariate Gaussian distribution as well as a function to generate missing data (both randomly and non-randomly). For comparison reasons, the package also contains several wrapper functions for the imputation of non-responses that are missing at random.

This package adopts tipping-point theory to transcriptome profiles to help unravel disease regulatory trajectory.

This package interfaces R with the graphviz library for plotting R graph objects from the graph package.

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 exposes a C elegans annotation database generated from UCSC by exposing these as TxDb objects.

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 MsFeature package defines functionality for Mass Spectrometry features. This includes functions to group (LC-MS) features based on some of their properties, such as retention time (coeluting features), or correlation of signals across samples. This package hence can be used to group features, and its results can be used as an input for the QFeatures package which allows aggregating abundance levels of features within each group. This package defines concepts and functions for base and common data types, implementations for more specific data types are expected to be implemented in the respective packages (such as e.g. xcms).

This package provides full genome sequences for Danio rerio (Zebrafish) as provided by UCSC (danRer10, Sep. 2014) and stored in Biostrings objects.

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.

RcisTarget identifies transcription factor binding motifs (TFBS) over-represented on a gene list. In a first step, RcisTarget selects DNA motifs that are significantly over-represented in the surroundings of the transcription start site (TSS) of the genes in the gene-set. This is achieved by using a database that contains genome-wide cross-species rankings for each motif. The motifs that are then annotated to TFs and those that have a high Normalized Enrichment Score (NES) are retained. Finally, for each motif and gene-set, RcisTarget predicts the candidate target genes (i.e. genes in the gene-set that are ranked above the leading edge).