Supplies AnnotationHub with EnsDb Ensembl-based annotation databases for all species. EnsDb SQLite databases are generated separately from Ensembl MySQL databases using functions from the ensembldb package employing the Ensembl Perl API.

This package contains pre-built human (GPL96) database of gene expression profiles. The gene expression data was downloaded from NCBI GEO, preprocessed and normalized consistently. The biological context of each sample was recorded and manually verified based on the sample description in GEO.

ASURAT is a software for single-cell data analysis. Using ASURAT, one can simultaneously perform unsupervised clustering and biological interpretation in terms of cell type, disease, biological process, and signaling pathway activity. Inputting a single-cell RNA-seq data and knowledge-based databases, such as Cell Ontology, Gene Ontology, KEGG, etc., ASURAT transforms gene expression tables into original multivariate tables, termed sign-by-sample matrices (SSMs).

This package implements an attribute-weighted aggregation algorithm which leverages peptide-spectrum match (PSM) attributes to provide a more accurate estimate of protein abundance compared to conventional aggregation methods. This algorithm employs pre-trained random forest models to predict the quantitative inaccuracy of PSMs based on their attributes. PSMs are then aggregated to the protein level using a weighted average, taking the predicted inaccuracy into account. Additionally, the package allows users to construct their own training sets that are more relevant to their specific experimental conditions if desired.

Data needed by the affycomp package.

Codelink ADME Rat 16-Assay Bioarray annotation data (chip adme16cod) assembled using data from public repositories.

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

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.

Studies including both microbiome and metabolomics data are becoming more common. Often, it would be helpful to integrate both datasets in order to see if they corroborate each others patterns. All vs all association is imprecise and likely to yield spurious associations. This package takes a knowledge-based approach to constrain association search space, only considering metabolite-function pairs that have been recorded in a pathway database. This package also provides a framework to assess differential association.

Colon normal tissue and cancer samples used in Corrada Bravo, et al. gene expression anti-profiles paper: BMC Bioinformatics 2012, 13:272 doi:10.1186/1471-2105-13-272. Measurements are z-scores obtained from the GeneExpression Barcode in the frma package.

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.

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).

AnVILBilling helps monitor AnVIL-related costs in R, using queries to a BigQuery table to which costs are exported daily. Functions are defined to help categorize tasks and associated expenditures, and to visualize and explore expense profiles over time. This package will be expanded to help users estimate costs for specific task sets.

APL is a package developed for computation of Association Plots (AP), a method for visualization and analysis of single cell transcriptomics data. The main focus of APL is the identification of genes characteristic for individual clusters of cells from input data. The package performs correspondence analysis (CA) and allows to identify cluster-specific genes using Association Plots. Additionally, APL computes the cluster-specificity scores for all genes which allows to rank the genes by their specificity for a selected cell cluster of interest.

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

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.

adverSCarial is an R Package designed for generating and analyzing the vulnerability of scRNA-seq classifiers to adversarial attacks. The package is versatile and provides a format for integrating any type of classifier. It offers functions for studying and generating two types of attacks, single gene attack and max change attack. The single-gene attack involves making a small modification to the input to alter the classification. The max-change attack involves making a large modification to the input without changing its classification. The CGD attack is based on an estimated gradient descent. against adversarial attacks. The package provides a comprehensive solution for evaluating the robustness of scRNA-seq classifiers against adversarial attacks.

Save SpatialExperiment objects and their images 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.

Supplies AnnotationHub with CytoBand information from UCSC. There is a track for each major organism. Giemsa-stained bands are commonly used to decorate chromosomal overviews in visualizations of genomic data.

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.

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).

Supplies AnnotationHub with MassBank metabolite/compound annotations bundled in CompDb SQLite databases. CompDb SQLite databases contain general compound annotation as well as fragment spectra representing fragmentation patterns of compounds ions. MassBank data is retrieved from https://massbank.eu/MassBank and processed using helper functions from the CompoundDb Bioconductor package into redistributable SQLite databases.

Store Google DeepMind AlphaMissense v2023 hg38 pathogenicity scores AnnotationHub Resource Metadata. Provide provenance and citation information for Google DeepMind AlphaMissense v2023 hg38 pathogenicity score AnnotationHub resources. Illustrate in a vignette how to access those resources.

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.