
Bioconductor Msbackendmassbank
Mass spectrometry (MS) data backend supporting import and export of MS/MS library...
Install
npx skills add bioMate-AI/biomate-bioconductor-kb --skill bioconductor-msbackendmassbank -g -a claude-code -y- Repository
- bioMate-AI/biomate-bioconductor-kb793
- Category
- Data and ML
- Updated
- 5mo ago
- License
- See repository
- Context cost
- Lightabout 864 tokens
- Runs scripts
- No, instructions only
What it does
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.
MsBackendMassbank
Workflows
Standard Workflow
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.
When to Use
- Importing and exporting MS/MS library spectra from MassBank record files (plain text format) into
Spectraobjects. - Querying and interacting directly with a local MassBank SQL database (MySQL or SQLite) using
MsBackendMassbankSql. - Comparing spectra similarity and generating mirror plots using
compareSpectraandplotSpectraMirror.
When NOT to Use
- For raw LC-MS data processing (e.g., peak picking, retention time correction), use
xcms. - For handling non-MassBank formats like mzML or mzXML without MassBank metadata, use standard
Spectrabackends likeMsBackendMzR.
Data Requirements
- Plain text files in MassBank record format (one file per spectrum), or a local SQL database containing MassBank release dumps.
