# Msbackendmassbank

> MsBackendMassbank

- Skill: `biomate-ai/msbackendmassbank` (Agent Skill)
- Install (CLI): `npx skillmds@latest add biomate-ai/msbackendmassbank`
- Raw SKILL.md: https://api.skillmd.com/api/skills/biomate-ai/msbackendmassbank/raw
- Safety review: pending
- Works with: Claude Code, Claude.ai, OpenAI Codex
- Category: Coding & Dev Tools
- Author: biomate-ai (https://skillmd.com/u/biomate-ai)
- Updated: 2026-09-17
- Page: https://skillmd.com/skills/biomate-ai/msbackendmassbank

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# 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.

```r
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 `Spectra` objects.
- Querying and interacting directly with a local MassBank SQL database (MySQL or SQLite) using `MsBackendMassbankSql`.
- Comparing spectra similarity and generating mirror plots using `compareSpectra` and `plotSpectraMirror`.

## 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 `Spectra` backends like `MsBackendMzR`.

## Data Requirements
- Plain text files in MassBank record format (one file per spectrum), or a local SQL database containing MassBank release dumps.

## Key Parameters
- **source**: An instance of `MsBackendMassbank()` or `MsBackendMassbankSql()` specifying the data source.
- **backend**: An instance of `MsBackendDataFrame()` or other `Spectra` backends to store the imported data.
- **nonStop** (FALSE): If `TRUE`, prevents the import from stopping when problematic MassBank files are encountered.
- **metaBlock**: Configured blocks of metadata fields to import, generated by `metaDataBlocks(ac = TRUE, ms = TRUE)`.
- **ppm** (40): Parts-per-million tolerance for m/z matching in `compareSpectra` or `plotSpectraMirror`.

## Best Practices
- Set `nonStop = TRUE` when importing a large number of MassBank files to prevent a single malformed file from crashing the process.
- Use `dropNaSpectraVariables` to remove imported spectra variables that contain only missing values across all spectra.
- Use `MsBackendMassbankSql` for large-scale analyses to fetch data on demand from a local SQL database instead of loading thousands of text files into memory.

## Common Pitfalls
- Attempting parallel processing with `MsBackendMassbankSql`: The database connection cannot be shared across parallel processes, so parallel processing is silently disabled.
- Slow import times: Importing all metadata blocks can be slow; customize the imported blocks using `metaDataBlocks` or use the SQL backend.

## Alternatives
- `Spectra` with `MsBackendDataFrame` for in-memory generic spectrum handling.
- `MsCoreUtils` for low-level mass spectrometry helper functions.

## Citations
- Witting, Rainer, Stravs 2026, MsBackendMassbank (vignette documentation)

## References
- Homepage: bioconductor.org/packages/MsBackendMassbank
- Vignette: https://bioconductor.org/packages/release/bioc/vignettes/MsBackendMassbank/inst/doc/MsBackendMassbank.html