Rawrr spectral data retrieval

rawrr-spectral-data-retrieval

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Summary

Programmatically extract spectral data (m/z, intensity, retention time, scan metadata) directly from Thermo Fisher Scientific Orbitrap .raw files using the rawrr R package, without requiring external file conversion. This enables modular end-to-end proteomics pipelines in R that operate on vendor-native binary data.

When to use

You have Thermo Orbitrap .raw files and need to access raw spectral data (individual MS1 or MS2 scans, base-peak values, chromatogram traces, retention times, or scan-level metadata) for custom analysis, visualization, or integration into an R-based pipeline. Use this when external preprocessing tools (MaxQuant, Skyline) are not appropriate, or when you need programmatic access to scan-level details for quality control, method optimization, or modular downstream processing.

When NOT to use

• Input data is already in an open exchange format (mzML, mzXML, NetCDF); use format-agnostic tools like MSnbase or Spectra instead.
• You only need high-level statistical analysis (e.g., differential abundance, pathway analysis); use MaxQuant → MSstats or MSqRob rather than low-level spectral access.
• Your .raw files are from non-Thermo instruments (e.g., Waters, Bruker, Agilent); rawrr only supports Orbitrap instruments and the RawFileReader API.

Inputs

• Thermo Fisher Scientific Orbitrap .raw file (binary)
• Scan index data.frame (output from readIndex(); optional pre-filtered subset)
• Vector of scan numbers or MS level filter criteria

Outputs

• rawrrSpectrum or rawrrSpectrumSet R object(s) containing m/z, intensity, retention time, scan metadata
• Tabular data (data.frame or CSV) with columns: scan_number, retention_time, base_peak_mz, base_peak_intensity, MS_level
• rawrrChromatogram object (if chromatogram data is extracted)

How to apply

First, install the rawrr R package and its compiled executable wrapper (rawrr::installRawrrExe()), which wraps the vendor RawFileReader .NET assembly and manages inter-process communication via temporary file I/O. Load the .raw file path and call readIndex() to generate a scan-level data.frame that indexes all scans with their MS level, scan type, retention time, and other metadata. Subset this index by MS level (ms == 1 for precursor scans, ms == 2 for fragment scans) or scan type as needed. Then iterate over scan numbers of interest and call readSpectrum() on each to retrieve individual rawrrSpectrum objects; extract desired properties (m/z, intensity, base-peak) using accessor functions. Aggregate the results into a table and export. The rationale is that rawrr avoids lossy conversion to exchange formats (mzML) and preserves full access to vendor-specific metadata and high-resolution data.

Related tools

• RawFileReader (Vendor-provided .NET assembly that implements low-level binary .raw file parsing; wrapped by rawrr via C# interop and system calls) — https://github.com/thermofisherlsms/RawFileReader
• rawrr (R package that wraps RawFileReader, provides high-level accessor functions (readIndex, readSpectrum, readChromatogram, readFileHeader), and manages temporary file I/O for data exchange) — https://github.com/fgcz/rawrr
• MsBackendRawFileReader (Bioconductor backend that integrates rawrr with the Spectra package, enabling on-disk spectral data access via standardized MsBackend interface) — https://github.com/cpanse/MsBackendRawFileReader
• Spectra (Bioconductor package providing unified S4 classes and methods for spectral data; can use MsBackendRawFileReader to read from .raw files) — https://bioconductor.org/packages/Spectra/
• tartare (Bioconductor ExperimentData package providing test .raw files for rawrr development and validation)

Examples

rawrr::installRawrrExe(); idx <- rawrr::readIndex(rawrr::sampleFilePath()); ms1_idx <- subset(idx, ms == 1); sp <- rawrr::readSpectrum(rawrr::sampleFilePath(), scan=ms1_idx$scan[1]); bp_mz <- sp@mz[which.max(sp@intensity)]; bp_int <- max(sp@intensity)

Evaluation signals

• Scan index data.frame contains expected number of rows (one per scan) with non-null columns: ms (1 or 2), rt (retention time in minutes), and scanType; verify row count matches instrument log.
• readSpectrum() returns valid rawrrSpectrum objects with m/z and intensity vectors of equal length; check object structure using str() or summary().
• Base-peak extraction yields m/z and intensity pairs where intensity > 0 and m/z is within instrument mass range (e.g., 100–2000 m/z for typical proteomics); spot-check against raw vendor software or alternative parsers.
• Aggregate table has no missing values for filtered scans; retention times increase monotonically across scan sequence; CSV writes successfully with correct delimiter and encoding.
• Extracted chromatogram data (if used) shows expected retention time distribution and peak shapes consistent with LC method parameters (e.g., peak width, gradient length).

Limitations

• rawrr is Windows/Linux/macOS compatible only on systems with .NET runtime installed; requires explicit executable installation via rawrr::installRawrrExe().
• Inter-process communication via temporary file I/O can incur I/O overhead for very large numbers of scans; batch processing recommended over single-scan iteration in performance-critical pipelines.
• rawrr provides access to Orbitrap instruments only (Thermo Fisher Scientific); not compatible with Waters, Bruker, Agilent, or other vendor raw formats.
• Future alignment with R for Mass Spectrometry initiative (exchangeable backends) is planned but not yet fully implemented, limiting long-term stability guarantees.
• Big computational proteomics capabilities in R are still being developed; current rawrr is suitable for method optimization and quality control but not yet optimized for large-scale repository-scale reanalysis.

Evidence

• [other] rawrr provides readIndex() to generate a scan index data.frame, readSpectrum() to read spectral data, and accessor functions to programmatically extract scan properties: "rawrr provides readIndex() to generate a scan index data.frame, readSpectrum() to read spectral data, and accessor functions to programmatically extract scan properties"
• [methods] R functions requesting access to data stored in binary raw files invoke compiled C# wrapper methods using a system call. Extracted information is written to a temporary location on harddrive, read back into memory and parsed into R objects: "R functions requesting access to data stored in binary raw files (reader family functions listed in Table 1) invoke compiled C# wrapper methods using a system call. [...] In order to return extracted"
• [results] By using the readIndex() function a data.frame that indexes all scans found in a raw file is returned: "By using the readIndex() function a data.frame that indexes all scans found in a raw file is returned"
• [results] Individual scans or scan collections (sets) can be read by the function readSpectrum(): "Individual scans or scan collections (sets) can be read by the function readSpectrum()"
• [intro] A library providing raw data reading would finally close the gap and facilitate modular end-to-end analysis pipeline development in R: "We strongly believe that a library providing raw data reading would finally close the gap and facilitate modular end-to-end analysis pipeline development in R"
• [readme] rawrr wraps the functionality of the RawFileReader .NET assembly. Provides access to proprietary Thermo Fisher Scientific Orbitrap instrument data: "The package provides access to proprietary Thermo Fisher Scientific Orbitrap instrument data as a stand-alone R package or serves as MsRawFileReaderBackend for the Bioconductor Spectra package. rawrr"
• [results] using only MS1-level scans: "Filter MS scans using ms filter; using only MS1-level scans"