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.

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.

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.

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

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 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.

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.

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).

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.

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.

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.

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.

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.

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.

This package provides access to mapping and results objects generated by the AssessORF package, as well as the genome sequences for the strains corresponding to those objects.

Data needed by the affycomp package.

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

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

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.

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.

Builds upon the existing ArtifactDB project, expending alabaster.spatial for language agnostic on disk serialization of SpatialFeatureExperiment.

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.

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).