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Published 2025 | Version v6
Software Open

vdhooftcompmet/MS2LDA 2.0

Authors/Creators

  • 1. ROR icon Wageningen University & Research
  • 2. ROR icon University of Glasgow

Contributors

Project leader:

Project member:

  • 1. ROR icon Wageningen University & Research
  • 2. ROR icon University of Glasgow

Description

For running the automated guidance annotation (SAG) in MS2LDA 2.0 you need to download the following files:

Please extract Spec2Vec.zip, and inside it you can find:
150225_CleanedLibraries_Spec2Vec_pos_embeddings.npy, 150225_Spec2Vec_pos_CleanedLibraries.model, 150225_Spec2Vec_pos_CleanedLibraries.model.wv.vectors.npy, 150225_CombLibraries_spectra.db, and 150225_Spec2Vec_pos_CleanedLibraries.model.syn1neg.npy.

Place all these into a single folder for Spec2Vec/positive_mode/*

The command ms2lda --only-download can be used to download these model files and place them in the right location.

The rest of the files are the results for the MS2LDA 2.0 manuscript.

Files

Spec2Vec.zip

Files (3.8 GB)

Name Size Download all
md5:3b200e51522a7abfbd5c35ac8bc6b5b4
9.3 MB Download
md5:aae08b4ebb833688f58ecce6a16e5fbd
33.7 MB Download
md5:af2e2f5105e25168eb5ae286e044028f
44.0 MB Download
md5:4ea2b1442fd00e03d50c86fdbc6a3bed
17.5 MB Download
md5:ea0adc887dfec8a32ff2413dfd6ce4e4
1.7 GB Download
md5:37e75bdd689007951a607562485fd93e
2.0 GB Preview Download

Additional details

Related works

Is supplement to
Software: https://github.com/vdhooftcompmet/MS2LDA/tree/1.0.1 (URL)

Software

Repository URL
https://github.com/vdhooftcompmet/MS2LDA