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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Mass spectrometry (MS) data backend supporting import and export of MS/MS library spectra from MassBank record files. Different backends are available that allow handling of data in plain MassBank text file format or allow also to interact directly with MassBank SQL databases. Objects from this package are supposed to be used with the Spectra Bioconductor package. This package thus adds MassBank support to the Spectra package.
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실행 점수 미검증
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Mass spectrometry (MS) data backend supporting import and export of MS/MS library spectra from MassBank record files. Different backends are available that allow handling of data in plain MassBank text file format or allow also to interact directly with MassBank SQL databases. Objects from this package are supposed to be used with the Spectra Bioconductor package. This package thus adds MassBank support to the Spectra package.
library(Spectra)
library(MsBackendMassbank)
fls <- dir(system.file("extdata", package = "MsBackendMassbank"), full.names = TRUE, pattern = "txt$")
sps <- Spectra(fls, source = MsBackendMassbank(), backend = MsBackendDataFrame(), nonStop = TRUE)
sps <- dropNaSpectraVariables(sps)
Input: A character vector of paths to MassBank text files. Output: A Spectra object containing the imported mass spectrometry data.
Spectra objects.MsBackendMassbankSql.compareSpectra and plotSpectraMirror.xcms.Spectra backends like MsBackendMzR.MsBackendMassbank() or MsBackendMassbankSql() specifying the data source.MsBackendDataFrame() or other Spectra backends to store the imported data.TRUE, prevents the import from stopping when problematic MassBank files are encountered.metaDataBlocks(ac = TRUE, ms = TRUE).compareSpectra or plotSpectraMirror.nonStop = TRUE when importing a large number of MassBank files to prevent a single malformed file from crashing the process.dropNaSpectraVariables to remove imported spectra variables that contain only missing values across all spectra.MsBackendMassbankSql for large-scale analyses to fetch data on demand from a local SQL database instead of loading thousands of text files into memory.MsBackendMassbankSql: The database connection cannot be shared across parallel processes, so parallel processing is silently disabled.metaDataBlocks or use the SQL backend.Spectra with MsBackendDataFrame for in-memory generic spectrum handling.MsCoreUtils for low-level mass spectrometry helper functions.아직 리뷰가 없습니다. 사용해 본 소감을 남겨 주세요.
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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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