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A collection of Galaxy-related training material

Home Page: https://training.galaxyproject.org

License: MIT License

Shell 0.54% JavaScript 23.06% Ruby 4.26% Python 1.01% CSS 0.35% TeX 9.61% Makefile 0.16% HTML 57.93% Mako 0.05% HCL 0.06% Dockerfile 0.21% SCSS 0.62% Jupyter Notebook 1.78% Common Workflow Language 0.36%

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Contributors

abretaud avatar anuprulez avatar beatrizserrano avatar bebatut avatar bgruening avatar camila-goclowski avatar claraurf avatar fubar2 avatar gallardoalba avatar guerler avatar hexylena avatar lecorguille avatar lldelisle avatar malloryfreeberg avatar marie59 avatar martenson avatar mblue9 avatar melkeb avatar mtekman avatar natefoo avatar nekrut avatar nomadscientist avatar nsoranzo avatar polkhe avatar shiltemann avatar simonbray avatar subinamehta avatar wee-snufkin avatar wm75 avatar yvanlebras avatar

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training-material's Issues

GTN rcx-aplcms: create picture illustrating weak signal

We need to include a figure showing recovery of weak signals. What would be nice is to have 3D surface plot (mz, rt, intensity) with a peak with low intensity. This could be then highlighted and compared to a metadata aligned table as the missing feature.

GTN: Molecular networking with matchms & cytoscape

This galaxy training should describe how - after obtaining (annotated) spectra in msp format - we can use matchms for molecular networking and similarity computation as well as filtering of our msp libraries.

  • Get started with GitPod and GTN training
  • Assemble preliminary workflow
  • Section on molecular networking
  • Section on spectral matching & MSP data
  • Section on networking tool -> future
  • Section on cytoscape in Galaxy

Peak detection with recetox-aplcms Galaxy Training

This should be a small Galaxy training giving a more in-depth description on how to use the recetox-aplcms tool for peak detection for GC & LC-MS data, similar to the original tutorial here.

  • GTN rcx-apclms: write introduction about package
  • #7
  • #6
  • GTN rcx-aplcms: Section on peak detection step
  • #4
  • GTN rcx-aplcms: Section on peak alignment
  • #5
  • GTN rcx-aplcms: Section on outputs

GC-HRMS data processing Galaxy Training

  • #1
  • Section on deconvolution with RAMClustR
  • Section on batch correction with WaveICA
  • Section on RI addition with RIAssigner
  • Section on matching with matchms
  • Section on output filtering and representation

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