The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.
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Provides utilities for identifying drug-target interactions for sets of small molecule or gene/protein identifiers. The required drug-target interaction information is obained from a local SQLite instance of the ChEMBL database. ChEMBL has been chosen for this purpose, because it provides one of the most comprehensive and best annotatated knowledge resources for drug-target information available in the public domain.
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Provides utilities for identifying drug-target interactions for sets of small molecule or gene/protein identifiers. The required drug-target interaction information is obained from a local SQLite instance of the ChEMBL database. ChEMBL has been chosen for this purpose, because it provides one of the most comprehensive and best annotatated knowledge resources for drug-target information available in the public domain.
library(drugTargetInteractions)
chembldb <- system.file("extdata", "chembl_sample.db", package="drugTargetInteractions")
resultsPath <- system.file("extdata", "results", package="drugTargetInteractions")
config <- genConfig(chemblDbPath=chembldb, resultsPath=resultsPath)
downloadUniChem(config=config)
cmpIdMapping(config=config)
queryBy <- list(molType="cmp", idType="chembl_id", ids=c("CHEMBL17", "CHEMBL19"))
qresult1 <- drugTargetAnnot(queryBy, config=config)
Input: A list containing query molecule/protein IDs and a configuration object. Output: A data.frame of drug-target annotations.
getUniprotIDs or paralogs via getParalogs.drugTargetBioactivity.Rcpi or external tools.chembl_sample.db for testing).molType (e.g., "cmp", "protein", "gene"), idType (e.g., "chembl_id", "UniProt_ID", "ensembl_gene_id"), and a character vector of ids.genConfig.genConfig.getUniprotIDs.getUniprotIDs.getUniprotIDs.getDrugTarget.genConfig to set up paths to the local ChEMBL SQLite database and output directories before running queries.downloadUniChem and cmpIdMapping to download and prepare compound identifier mapping tables.getParalogs instead of getUniprotIDs when faster execution and wider evolutionary distances are preferred.runDrugTarget_Annot_Bioassay.chembl_sample.db for real analyses: replace the path in genConfig with the path to a full downloaded ChEMBL SQLite database.getUniprotIDs: set chunksize=1 only when tracking query Ensembl gene ID information is strictly required, or use getParalogs as a faster alternative.tapply to collapse Ensembl IDs when mapping back to UniProt IDs.biomaRt for general gene/protein annotation and paralog retrieval.UniProt.ws for direct web-based UniProt ID mapping.ensembldb for local genomic and protein feature mapping.还没有评价。欢迎分享你的使用感受。
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The package contains functions for exploratory oligonucleotide array analysis. The dependence on tkWidgets only concerns few convenience functions. 'affy' is fully functional without it.
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This tool uses the label-tree function from HyPhy to annotate a phylogenetic tree. It allows users to select a subset of leaves using either a regular expression or a list of sequence names, and then apply a specified label to these selecte
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This package provides a client for the Bioconductor AnnotationHub web resource. The AnnotationHub web resource provides a central location where genomic files (e.g., VCF, bed, wig) and other resources from standard locations (e.g., UCSC, En
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apeglm provides Bayesian shrinkage estimators for effect sizes for a variety of GLM models, using approximation of the posterior for individual coefficients.
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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).
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AUCell allows to identify cells with active gene sets (e.g. signatures, gene modules...) in single-cell RNA-seq data. AUCell uses the "Area Under the Curve" (AUC) to calculate whether a critical subset of the input gene set is enriched with
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