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 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.

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.

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

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.

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.

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.

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

Data needed by the affycomp package.

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.

Fast annotation of genomic peaks using DNA interaction data by constructing interaction networks with igraph, where peaks overlapping any node in a connected subgraph are annotated with all genes in that subgraph. The annotation evidence could be visualized as either a network graph or a genomic track integrated with gene annotation information.

This package contains pre-built mouse (GPL1261) 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 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.

iFull genome sequences for Apis mellifera (Honey Bee) as provided by BeeBase (assembly4, Feb. 2008) and stored in Biostrings objects.

This package contains several sets of omics data including Gene Expression (ExpressionSet), Methylation (GenomicRatioSet), Proteome and Exposome (ExposomeSet). This data is used in vignettes and exaples at MEAL, MultiDataSet and omicRexposome.

The package contains data of the Primary Blood Cancer Encyclopedia (PACE) project together with a complete executable transcript of the statistical analysis and reproduces figures presented in the paper "Drug-perturbation-based stratification of blood cancer" by Dietrich S, Oleś M, Lu J et al., J. Clin. Invest. (2018) 128(1):427-445. doi:10.1172/JCI93801.

bettr provides a set of interactive visualization methods to explore the results of a benchmarking study, where typically more than a single performance measures are computed. The user can weight the performance measures according to their preferences. Performance measures can also be grouped and aggregated according to additional annotations.

Full genome sequences for Danio rerio (Zebrafish) as provided by UCSC (danRer6, Dec. 2008) and stored in Biostrings objects.

Full genome sequences for Danio rerio (Zebrafish) as provided by UCSC (danRer6, Dec. 2008) and stored in Biostrings objects. The sequences are the same as in BSgenome.Drerio.UCSC.danRer6, except that each of them has the 4 following masks on top: (1) the mask of assembly gaps (AGAPS mask), (2) the mask of intra-contig ambiguities (AMB mask), (3) the mask of repeats from RepeatMasker (RM mask), and (4) the mask of repeats from Tandem Repeats Finder (TRF mask). Only the AGAPS and AMB masks are "active" by default.

the R package BioNAR, developed to step by step analysis of PPI network. The aim is to quantify and rank each protein’s simultaneous impact into multiple complexes based on network topology and clustering. Package also enables estimating of co-occurrence of diseases across the network and specific clusters pointing towards shared/common mechanisms.