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.

Six arrays. Three from amplified RNA, three from the typical procedure.

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.

The package provides a comprehensive mapping table of metabolites and proteins linked to PathBank pathways. The tables include HMDB, KEGG, ChEBI, CAS, Drugbank, Uniprot IDs. The tables are provided for each of the 10 species ("Homo sapiens", "Escherichia coli", "Mus musculus", "Arabidopsis thaliana", "Saccharomyces cerevisiae", "Bos taurus", "Caenorhabditis elegans", "Rattus norvegicus", "Drosophila melanogaster", and "Pseudomonas aeruginosa"). These table information can be used for Metabolite Set (and other) Enrichment Analysis.

Visualisation of peptide isotopic peaks and SIP peptide spectra match (PSM). Filtration of high quality PSM. Accurate isotopic abundance calculation of peptide and metabolites. Visualisation of SIP proteomics results.

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.

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.

Save common bioinformatics file formats within the alabaster framework. This includes BAM, BED, VCF, bigWig, bigBed, FASTQ, FASTA and so on. We save and load additional metadata for each file, and we support linkage between each file and its corresponding index.

The ASURI (Analysis of SUrvival and patients RIsk prediction based on gene signatures) package discovers marker genes that are related to risk prediction capabilities and to a clinical variable of interest. It uses two main steps, including subsampling glmnet and unicox. The package implements robust functions to discover survival markers related to a clinical phenotype and to predict a risk score, allowing to study the patient's risk based on the gene signatures. Several plots are provided to visualise the relevance of the genes, the risk score, and patient stratification, as well as a robust version of the Kaplan-Meier curves.

This package contains annotation data files and sample data files of Affymetrix file formats. The files originate from the Affymetrix Fusion SDK distribution and other official sources.

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 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.

Perform 3'UTR APA, Intronic APA and gene expression analysis using RNA-seq data.

The appreci8R is an R version of our appreci8-algorithm - A Pipeline for PREcise variant Calling Integrating 8 tools. Variant calling results of our standard appreci8-tools (GATK, Platypus, VarScan, FreeBayes, LoFreq, SNVer, samtools and VarDict), as well as up to 5 additional tools is combined, evaluated and filtered.

Use this package to create or update AnVIL workspaces from resources such as R / Bioconductor packages. The metadata about the package (e.g., select information from the package DESCRIPTION file and from vignette YAML headings) are used to populate the DASHBOARD'. Vignettes are translated to python notebooks ready for evaluation in AnVIL.

Store Google DeepMind AlphaMissense v2023 hg19 pathogenicity scores AnnotationHub Resource Metadata. Provide provenance and citation information for Google DeepMind AlphaMissense v2023 hg19 pathogenicity score AnnotationHub resources. Illustrate in a vignette how to access those resources.

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

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.

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.

The package prepares input scATAC-seq data and adapts for copy number variance profiling with InferCNV package usage. It has also various paramters to control the analysis (e.g. external normal reference usage, meta-cells, bin size, etc) and custom plot visualizations.

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.

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).

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.