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Releases: hiows/MALDIassist-py

v1.0.0

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@hiows hiows released this 16 Jul 12:42

First stable release of maldiassist (Python port of MALDIassist).

Full Changelog: v0.2.2...v1.0.0

v0.2.2

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@github-actions github-actions released this 13 Jul 13:51

Full Changelog: v0.2.1...v0.2.2

v0.2.1

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@github-actions github-actions released this 13 Jul 13:01

Full Changelog: v0.2.0...v0.2.1

v0.2.0

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@github-actions github-actions released this 13 Jul 12:36

Full Changelog: v0.1.0...v0.2.0

v0.1.0

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@hiows hiows released this 13 Jul 11:57

maldiassist v0.1.0

First release of maldiassist, a pure-Python port of the
MALDIassist R package (v0.1.3, R + Rcpp/C++)
that reproduces the same algorithms and numerical results.

Highlights

  • Pure-Python implementation (numpy, scipy, pandas) — no compiler required.
  • Full five-step MALDI-TOF workflow, matching the original R package:
    • Bruker Flex raw-data loading (load_maldi_spectra)
    • Preprocessing: Savitzky-Golay smoothing + SNIP/TopHat baseline (preprocess_maldi_spectra)
    • Kernel-regression peak detection incl. shoulder peaks (find_peaks / find_peaks_spectra)
    • Peak metrics and filtering (filter_peaks / filter_peaks_spectra)
    • Cohort analysis: alignment, frequent m/z, matched matrix, significance testing
    • Visualization (visualize_spectrum/spectra, heatmap_matched_matrix)

Numerical fidelity

Validated step by step against ground truth produced by running the original R
package on the TestData set, achieving an exact match within floating-point
tolerance. Kernel summation uses the same sequential accumulation order as R's
Rcpp loop to preserve tie-breaking in extremum selection.

Installation

pip install "git+https://github.com/hiows/MALDIassist-py.git"
pip install "maldiassist[viz] @ git+https://github.com/hiows/MALDIassist-py.git"  # with matplotlib

Requires Python 3.9+.