`orthosData` is the companion ExperimentData package to the `orthos` R package for mechanistic studies using differential gene expression experiments. It provides functions for retrieval from ExperimentHub and local caching of the models and datasets used internally in orthos.

Genome wide annotation for Xenopus, primarily based on mapping using Entrez Gene identifiers.

Data files used as examples and for testing of the software provided in the optimalFlow package.

This package allows users to control the false discovery rate (FDR) or familywise error rate (FWER) for online multiple hypothesis testing, where hypotheses arrive in a stream. In this framework, a null hypothesis is rejected based on the evidence against it and on the previous rejection decisions.

Genome wide annotation for Malaria, primarily based on mapping using Entrez Gene identifiers.

This package provides a platform for Operational Taxonomic Unit based analysis.

R package for analysis of transcript and translation features through manipulation of sequence data and NGS data like Ribo-Seq, RNA-Seq, TCP-Seq and CAGE. It is generalized in the sense that any transcript region can be analysed, as the name hints to it was made with investigation of ribosomal patterns over Open Reading Frames (ORFs) as it's primary use case. ORFik is extremely fast through use of C++, data.table and GenomicRanges. Package allows to reassign starts of the transcripts with the use of CAGE-Seq data, automatic shifting of RiboSeq reads, finding of Open Reading Frames for whole genomes and much more.

This package translates microarray expression data into metadata of reduced dimension. It provides various sample-centered and group-centered visualizations, sample similarity analyses and functional enrichment analyses. The underlying SOM algorithm combines feature clustering, multidimensional scaling and dimension reduction, along with strong visualization capabilities. It enables extraction and description of functional expression modules inherent in the data.

An implementation of methods for designing, evaluating, and comparing primer sets for multiplex PCR. Primers are designed by solving a set cover problem such that the number of covered template sequences is maximized with the smallest possible set of primers. To guarantee that high-quality primers are generated, only primers fulfilling constraints on their physicochemical properties are selected. A Shiny app providing a user interface for the functionalities of this package is provided by the openPrimeRui package.

This package provides a package for the orthology prediction data download from OMA database.

This package provides functions for normalisation of two-color microarrays by optimised local regression and for detection of artefacts in microarray data.

This package perform weighted-pvalue based multiple hypothesis test and provides corresponding information such as ranking probability, weight, significant tests, etc . To conduct this testing procedure, the testing method apply a probabilistic relationship between the test rank and the corresponding test effect size.

omicsPrint provides functionality for cross omic genetic fingerprinting, for example, to verify sample relationships between multiple omics data types, i.e. genomic, transcriptomic and epigenetic (DNA methylation).

The software uses the copy number segments from a text file and identifies all chromosome arms that are globally altered and computes various genome-wide scores. The following HRD scores (characteristic of BRCA-mutated cancers) are included: LST, HR-LOH, nLST and gLOH. the package is tailored for the ThermoFisher Oncoscan assay analyzed with their Chromosome Alteration Suite (ChAS) but can be adapted to any input.

OGRE calculates overlap between user defined genomic region datasets. Any regions can be supplied i.e. genes, SNPs, or reads from sequencing experiments. Key numbers help analyse the extend of overlaps which can also be visualized at a genomic level.

This packages provides C++ header files for developers wishing to create R packages that processes BAM files. ompBAM automates file access, memory management, and handling of multiple threads behind the scenes', so developers can focus on creating domain-specific functionality. The included vignette contains detailed documentation of this API, including quick-start instructions to create a new ompBAM-based package, and step-by-step explanation of the functionality behind the example packaged included within ompBAM.

omicsViewer visualizes ExpressionSet (or SummarizedExperiment) in an interactive way. The omicsViewer has a separate back- and front-end. In the back-end, users need to prepare an ExpressionSet that contains all the necessary information for the downstream data interpretation. Some extra requirements on the headers of phenotype data or feature data are imposed so that the provided information can be clearly recognized by the front-end, at the same time, keep a minimum modification on the existing ExpressionSet object. The pure dependency on R/Bioconductor guarantees maximum flexibility in the statistical analysis in the back-end. Once the ExpressionSet is prepared, it can be visualized using the front-end, implemented by shiny and plotly. Both features and samples could be selected from (data) tables or graphs (scatter plot/heatmap). Different types of analyses, such as enrichment analysis (using Bioconductor package fgsea or fisher's exact test) and STRING network analysis, will be performed on the fly and the results are visualized simultaneously. When a subset of samples and a phenotype variable is selected, a significance test on means (t-test or ranked based test; when phenotype variable is quantitative) or test of independence (chi-square or fisher’s exact test; when phenotype data is categorical) will be performed to test the association between the phenotype of interest with the selected samples. Additionally, other analyses can be easily added as extra shiny modules. Therefore, omicsViewer will greatly facilitate data exploration, many different hypotheses can be explored in a short time without the need for knowledge of R. In addition, the resulting data could be easily shared using a shiny server. Otherwise, a standalone version of omicsViewer together with designated omics data could be easily created by integrating it with portable R, which can be shared with collaborators or submitted as supplementary data together with a manuscript.

Genome wide annotation for Arabidopsis, primarily based on mapping using TAIR identifiers.

This package provides genome-wide annotation for Heterorhabditis bacteriophora, primarily based on mapping using custom gene identifiers. This OrgDb annotation package is intended for use with AnnotationDbi-based tools and supports querying of gene identifiers and related metadata.

Optimal-transport techniques applied to supervised flow cytometry gating.

This package provides the output of running Salmon on a set of 12 RNA-seq samples from King & Klose, "The pioneer factor OCT4 requires the chromatin remodeller BRG1 to support gene regulatory element function in mouse embryonic stem cells", published in eLIFE, March 2017. For details on version numbers and how the samples were processed see the package vignette.

Genome wide annotation for Pig, primarily based on mapping using Entrez Gene identifiers.

Genome wide annotation for Canine, primarily based on mapping using Entrez Gene identifiers.

FHCRC Nelson Lab OperonHumanV3 Annotation Data (OperonHumanV3) assembled using data from public repositories.