This package provides full genome sequences for Caenorhabditis elegans (Worm) as provided by UCSC (ce6, May 2008) and stored in Biostrings objects.

Single-cell RNA sequencing (scRNA-seq) methods are typically unable to quantify the expression levels of all genes in a cell, creating a need for the computational prediction of missing values (dropout imputation). Most existing dropout imputation methods are limited in the sense that they exclusively use the scRNA-seq dataset at hand and do not exploit external gene-gene relationship information. The ADImpute package proposes two methods to address this issue:

1. a gene regulatory network-based approach using gene-gene relationships learnt from external data;

2. a baseline approach corresponding to a sample-wide average.

ADImpute implements these novel methods and also combines them with existing imputation methods like DrImpute and SAVER. ADImpute can learn the best performing method per gene and combine the results from different methods into an ensemble.

This package provides a suite of helper functions for checking and manipulating TCGA data including data obtained from the curatedTCGAData experiment package. These functions aim to simplify and make working with TCGA data more manageable. Exported functions include those that import data from flat files into Bioconductor objects, convert row annotations, and identifier translation via the GDC API.

This package provides an integrated pipeline for the analysis of PAR-CLIP data. PAR-CLIP-induced transitions are first discriminated from sequencing errors, SNPs and additional non-experimental sources by a non- parametric mixture model. The protein binding sites (clusters) are then resolved at high resolution and cluster statistics are estimated using a rigorous Bayesian framework. Post-processing of the results, data export for UCSC genome browser visualization and motif search analysis are provided. In addition, the package integrates RNA-Seq data to estimate the False Discovery Rate of cluster detection. Key functions support parallel multicore computing. While wavClusteR was designed for PAR-CLIP data analysis, it can be applied to the analysis of other NGS data obtained from experimental procedures that induce nucleotide substitutions (e.g. BisSeq).

The stageR package allows automated stage-wise analysis of high-throughput gene expression data. The method is published in Genome Biology at https://genomebiology.biomedcentral.com/articles/10.1186/s13059-017-1277-0.

TFBSTools is a package for the analysis and manipulation of transcription factor binding sites. It includes matrices conversion between Position Frequency Matrix (PFM), Position Weight Matrix (PWM) and Information Content Matrix (ICM). It can also scan putative TFBS from sequence/alignment, query JASPAR database and provides a wrapper of de novo motif discovery software.

R-msigdb provides the Molecular Signatures Database in a R accessible objects. Signatures are stored in GeneSet class objects form the GSEABase package and the entire database is stored in a GeneSetCollection object. These data are then hosted on the ExperimentHub. Data used in this package was obtained from the MSigDB of the Broad Institute. Metadata for each gene set is stored along with the gene set in the GeneSet class object.

MetagenomeSeq is designed to determine features (be it OTU, species, etc.) that are differentially abundant between two or more groups of multiple samples. This package is designed to address the effects of both normalization and under-sampling of microbial communities on disease association detection and the testing of feature correlations.

FlowSOM offers visualization options for cytometry data, by using self-organizing map clustering and minimal spanning trees.

The purpose of this GO.db annotation package is to provide detailed information about the latest version of the Gene Ontologies.

This package provides a high-level R interface to CoreArray Genomic Data Structure (GDS) data files, which are portable across platforms with hierarchical structure to store multiple scalable array-oriented data sets with metadata information. It is suited for large-scale datasets, especially for data which are much larger than the available random-access memory. The gdsfmt package offers efficient operations specifically designed for integers of less than 8 bits, since a diploid genotype, like single-nucleotide polymorphism (SNP), usually occupies fewer bits than a byte. Data compression and decompression are available with relatively efficient random access. It is also allowed to read a GDS file in parallel with multiple R processes supported by the package parallel.

This package provides functions to compare two or more survival curves with:

• The Fleming-Harrington test for right-censored data based on permutations and on counting processes.

• An extension of the Fleming-Harrington test for interval-censored data based on a permutation distribution and on a score vector distribution.

This package provides tools to parse Illumina Sequence Analysis Viewer (SAV) files, access data, and generate QC plots.

This package provides an implementation of an algorithm for determining cluster count and membership by stability evidence in unsupervised analysis.

This package contains gene-level counts for a collection of public scRNA-seq datasets, provided as SingleCellExperiment objects with cell- and gene-level metadata.

This package performs unbiased cell type recognition from single-cell RNA sequencing data, by leveraging reference transcriptomic datasets of pure cell types to infer the cell of origin of each single cell independently.

This package provides a model for the clone size distribution of the TCR repertoire. Further, it permits comparative analysis of TCR repertoire libraries based on theoretical model fits.

The project is intended to support the use of sequins(synthetic sequencing spike-in controls) owned and made available by the Garvan Institute of Medical Research. The goal is to provide a standard library for quantitative analysis, modelling, and visualization of spike-in controls.

This package provides per-exon and per-gene read counts computed for selected genes from RNA-seq data that were presented in the article 'Conservation of an RNA regulatory map between Drosophila and mammals' by Brooks et al., Genome Research 2011.

The tRNA package allows tRNA sequences and structures to be accessed and used for subsetting. In addition, it provides visualization tools to compare feature parameters of multiple tRNA sets and correlate them to additional data. The tRNA package uses GRanges objects as inputs requiring only few additional column data sets.

Vizualize, analyze and explore networks using Cytoscape via R. Anything you can do using the graphical user interface of Cytoscape, you can now do with a single RCy3 function.

This package provides tools for the computationally efficient analysis of quantitative trait loci (QTL) data, including eQTL, mQTL, dsQTL, etc. The software in this package aims to support refinements and functional interpretation of members of a collection of association statistics on a family of feature/genome hypotheses.

This package provides a suite of methods for powerful and robust microbiome data analysis addressing zero-inflation, phylogenetic structure and compositional effects. The methods can be applied to the analysis of other (high-dimensional) compositional data arising from sequencing experiments.

This package provides tools for processing short read data from ChIPseq experiments.