This package provides functions for handling translating between different identifieres using the Biocore Data Team data-packages (e.g. org.Bt.eg.db).

This package provides a method to purify a cell type or cell population of interest from heterogeneous datasets. scGate package automatizes marker-based purification of specific cell populations, without requiring training data or reference gene expression profiles. scGate takes as input a gene expression matrix stored in a Seurat object and a GM, consisting of a set of marker genes that define the cell population of interest. It evaluates the strength of signature marker expression in each cell using the rank-based method UCell, and then performs kNN smoothing by calculating the mean UCell score across neighboring cells. kNN-smoothing aims at compensating for the large degree of sparsity in scRNAseq data. Finally, a universal threshold over kNN-smoothed signature scores is applied in binary decision trees generated from the user-provided gating model, to annotate cells as either “pure” or “impure”, with respect to the cell population of interest.

This package provides a set of tools and methods for making and manipulating transcript centric annotations. With these tools the user can easily download the genomic locations of the transcripts, exons and cds of a given organism, from either the UCSC Genome Browser or a BioMart database (more sources will be supported in the future). This information is then stored in a local database that keeps track of the relationship between transcripts, exons, cds and genes. Flexible methods are provided for extracting the desired features in a convenient format.

This package provides functions to estimate variance-mean dependence in count data from high-throughput nucleotide sequencing assays and test for differential expression based on a model using the negative binomial distribution.

This package implements a method that aims to identify enhancers on large scale. The STARR-seq data consists of two sequencing datasets of the same targets in a specific genome. The input sequences show which regions where tested for enhancers. Significant enriched peaks i.e. a lot more sequences in one region than in the input where enhancers in the genomic DNA are, can be identified. So the approach pursued is to call peak every region in which there is a lot more (significant in a binomial model) STARR-seq signal than input signal and propose an enhancer at that very same position. Enhancers then are called weak or strong dependent of there degree of enrichment in comparison to input.

This package provides a set of functions to create and interact with dynamic documents and vignettes.

This package provides a collection of tools for performing category analysis.

biomaRt provides an interface to a growing collection of databases implementing the http://www.biomart.org. The package enables retrieval of large amounts of data in a uniform way without the need to know the underlying database schemas or write complex SQL queries. Examples of BioMart databases are Ensembl, COSMIC, Uniprot, HGNC, Gramene, Wormbase and dbSNP mapped to Ensembl. These major databases give biomaRt users direct access to a diverse set of data and enable a wide range of powerful online queries from gene annotation to database mining.

This package annmap provides annotation mappings for Affymetrix exon arrays and coordinate based queries to support deep sequencing data analysis. Database access is hidden behind the API which provides a set of functions such as genesInRange(), geneToExon(), exonDetails(), etc. Functions to plot gene architecture and BAM file data are also provided.

This package provides tools to calculate functional similarities based on the pathways described on KEGG and REACTOME or in gene sets. These similarities can be calculated for pathways or gene sets, genes, or clusters and combined with other similarities. They can be used to improve networks, gene selection, testing relationships, and so on.

The motifStack package is designed for graphic representation of multiple motifs with different similarity scores. It works with both DNA/RNA sequence motifs and amino acid sequence motifs. In addition, it provides the flexibility for users to customize the graphic parameters such as the font type and symbol colors.

The canonical way to perform meta-analysis involves using effect sizes. When they are not available this package provides a number of methods for meta-analysis of significance values including the methods of Edgington, Fisher, Stouffer, Tippett, and Wilkinson; a number of data-sets to replicate published results; and a routine for graphical display.

This package provides Affymetrix HG_U95A Array annotation data (chip hgu95a) assembled using data from public repositories.

This is a package for saving Bioconductor data structures into file artifacts, and loading them back into memory. This is a more robust and 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.

This package is designed to facilitate comparison of automated gating methods against manual gating done in flowJo. This package allows you to import basic flowJo workspaces into BioConductor and replicate the gating from flowJo using the flowCore functionality. Gating hierarchies, groups of samples, compensation, and transformation are performed so that the output matches the flowJo analysis.

Lefser is an implementation in R of the popular "LDA Effect Size" (LEfSe) method for microbiome biomarker discovery. It uses the Kruskal-Wallis test, Wilcoxon-Rank Sum test, and Linear Discriminant Analysis to find biomarkers of groups and sub-groups.

This package provides ChIP-seq data for demonstration purposes in the chromstaR package.

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 mappings from Entrez gene identifiers to various annotations for the genome of the model mouse Mus musculus.

This package provides a set of annotation maps describing the entire Disease Ontology.

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

Read bigWig and bigBed files using libBigWig. This package provides lightweight access to the binary bigWig and bigBed formats developed by the UCSC Genome Browser group.

This package provides tools for calculating the Reproducibility-Optimized Test Statistic (ROTS) for differential testing in omics data.

The atSNP package performs affinity tests of motif matches with the SNP (single nucleotide polymorphism) or the reference genomes and SNP-led changes in motif matches.