Save MultiAssayExperiments into file artifacts, and load them back into memory. This is a more 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.

Affymetrix Affymetrix ATH1-121501 Array annotation data (chip ath1121501) assembled using data from public repositories.

Save BumpyMatrix objects into file artifacts, and load them back into memory. This is a more 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.

Annotation package for the implementation of the frozen Robust Multiarray Analysis procedure for Arabidopsis thaliana. This package was generated on the basis of frmaTools version 1.52.0.

This package was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was AG\_probe\_tab.

The package provides a comprehensive mapping table of metabolites linked to Wikipathways pathways. The tables include HMDB, KEGG, ChEBI, Drugbank, PubChem compound, ChemSpider, KNApSAcK, and Wikidata IDs plus CAS and InChIKey. The tables are provided for each of the 25 species ("Anopheles gambiae", "Arabidopsis thaliana", "Bacillus subtilis", "Bos taurus", "Caenorhabditis elegans", "Canis familiaris", "Danio rerio", "Drosophila melanogaster", "Equus caballus", "Escherichia coli", "Gallus gallus", "Gibberella zeae", "Homo sapiens", "Hordeum vulgare", "Mus musculus", "Mycobacterium tuberculosis", "Oryza sativa", "Pan troglodytes", "Plasmodium falciparum", "Populus trichocarpa", "Rattus norvegicus", "Saccharomyces cerevisiae", "Solanum lycopersicum", "Sus scrofa", "Zea mays"). These table information can be used for Metabolite Set Enrichment Analysis.

Assay for Transpose-Accessible Chromatin using sequencing (ATAC-seq) is a technique to assess genome-wide chromatin accessibility by probing open chromatin with hyperactive mutant Tn5 Transposase that inserts sequencing adapters into open regions of the genome. ATACseqTFEA is an improvement of the current computational method that detects differential activity of transcription factors (TFs). ATACseqTFEA not only uses the difference of open region information, but also (or emphasizes) the difference of TFs footprints (cutting sites or insertion sites). ATACseqTFEA provides an easy, rigorous way to broadly assess TF activity changes between two conditions.

Supplies AnnotationHub with some preprocessed sqlite, tibble, and data.table datasets of PubMed. All the datasets are generated by our Snakemake workflow [pubmed-workflow](https://github.com/rikenbit/pubmed-workflow). For the details, see the README.md of pubmed-workflow.

The AnVIL is a cloud computing resource developed in part by the National Human Genome Research Institute. The main cloud-based genomics platform deported by the AnVIL project is Terra. The AnVILWorkflow package allows remote access to Terra implemented workflows, enabling end-user to utilize Terra/ AnVIL provided resources - such as data, workflows, and flexible/scalble computing resources - through the conventional R functions.

This package contains pre-built human (GPL571) databases of gene expression profiles. The gene expression data was downloaded from NCBI GEO and preprocessed and normalized consistently. The biological context of each sample was recorded and manually verified based on the sample description in GEO.

This package contains ARACNe-inferred networks from TCGA tumor datasets. It also contains a function to export them into plain-text format.

Save variant calling SummarizedExperiment to file and load them back as VCF objects. This is a more 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 was automatically created by package AnnotationForge version 1.11.21. The probe sequence data was obtained from http://www.affymetrix.com. The file name was ATH1-121501\_probe\_tab.

1D NMR example spectra and additional data for use with the ASICS package. Raw 1D Bruker spectral data files were found in the MetaboLights database (https://www.ebi.ac.uk/metabolights/, study MTBLS1).

This package provides a package containing an environment representing the AG.CDF file.

Supplies AnnotationHub with `MeSHDb` NIH MeSH annotation databases for many species. All the SQLite files and metadata.csv are generated by our Snakemake workflow [mesh-workflow](https://github.com/rikenbit/mesh-workflow).

The AWAggregatorData package contains the data associated with the AWAggregator R package. It includes two pre-trained random forest models, one incorporating the average coefficient of variation as a feature, and the other one not including it. It also contains the PSMs in Benchmark Set 1~3 derived from the psm.tsv output files generated by FragPipe, which are used to train the random forest models.

The AlphaMissense publication <https://www.science.org/doi/epdf/10.1126/science.adg7492> outlines how a variant of AlphaFold / DeepMind was used to predict missense variant pathogenicity. Supporting data on Zenodo <https://zenodo.org/record/10813168> include, for instance, 71M variants across hg19 and hg38 genome builds. The AlphaMissenseR package allows ready access to the data, downloading individual files to DuckDB databases for exploration and integration into *R* and *Bioconductor* workflows.

ADAPT carries out differential abundance analysis for microbiome metagenomics data in phyloseq format. It has two innovations. One is to treat zero counts as left censored and use Tobit models for log count ratios. The other is an innovative way to find non-differentially abundant taxa as reference, then use the reference taxa to find the differentially abundant ones.

This package unifies access to Statistal Modeling of Omics Data. Across linear modeling engines (lm, lme, lmer, limma, and wilcoxon). Across coding systems (treatment, difference, deviation, etc). Across model formulae (with/without intercept, random effect, interaction or nesting). Across omics platforms (microarray, rnaseq, msproteomics, affinity proteomics, metabolomics). Across projection methods (pca, pls, sma, lda, spls, opls). Across clustering methods (hclust, pam, cmeans). Across survival methods (coxph, survdiff, coin). It provides a fast enrichment analysis implementation.

This package provides probe-level data for 20 HGU133A and 20 HGU133B arrays which are a subset of arrays from a large ALL study. The data is for the MLL arrays. This data was published in Mary E. Ross, Xiaodong Zhou, Guangchun Song, Sheila A. Shurtleff, Kevin Girtman, W. Kent Williams, Hsi-Che Liu, Rami Mahfouz, Susana C. Raimondi, Noel Lenny, Anami Patel, and James R. Downing (2003) Classification of pediatric acute lymphoblastic leukemia by gene expression profiling Blood 102: 2951-2959.

artMS provides a set of tools for the analysis of proteomics label-free datasets. It takes as input the MaxQuant search result output (evidence.txt file) and performs quality control, relative quantification using MSstats, downstream analysis and integration. artMS also provides a set of functions to re-format and make it compatible with other analytical tools, including, SAINTq, SAINTexpress, Phosfate, and PHOTON. Check [http://artms.org](http://artms.org) for details.

SonVariantsChr21 is a dataset of annotated genomic variants coming from Complete Genomics whole genome sequencing. Data comes from GIAB project, Ashkenazim Trio, sample HG002 run 1. Both vcf and annotated data frame are provided.

ASSIGN is a computational tool to evaluate the pathway deregulation/activation status in individual patient samples. ASSIGN employs a flexible Bayesian factor analysis approach that adapts predetermined pathway signatures derived either from knowledge-based literature or from perturbation experiments to the cell-/tissue-specific pathway signatures. The deregulation/activation level of each context-specific pathway is quantified to a score, which represents the extent to which a patient sample encompasses the pathway deregulation/activation signature.