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Develop
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michabirklbauer committed Dec 30, 2022
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35 changes: 35 additions & 0 deletions .github/workflows/python-app.yml
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# This workflow will lint with Python 3.10
# e.g. check for syntax errors and undefined names
# Reference workflow provided by (c) GitHub
# For more information see: https://help.github.com/actions/language-and-framework-guides/using-python-with-github-actions

name: peptide_matching_game

on:
push:
branches: [ master ]
pull_request:
branches: [ master ]

jobs:
build:

runs-on: ubuntu-latest

steps:
- uses: actions/checkout@v2
- name: Set up Python 3.10
uses: actions/setup-python@v2
with:
python-version: '3.10'
- name: Install dependencies
run: |
python -m pip install --upgrade pip
pip install flake8 pytest
if [ -f requirements.txt ]; then pip install -r requirements.txt; fi
- name: Lint with flake8
run: |
# stop the build if there are Python syntax errors or undefined names
flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics
# exit-zero treats all errors as warnings. The GitHub editor is 127 chars wide
flake8 . --count --exit-zero --max-complexity=10 --max-line-length=127 --statistics
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21 changes: 21 additions & 0 deletions LICENSE
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MIT License

Copyright (c) 2022 Micha Birklbauer, FH OOE Campus Hagenberg BIN Research Group

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
35 changes: 33 additions & 2 deletions README.md
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# peptide-matching-game
Peptide Matching Game Solution Browser
# Peptide Matching Game

A simple game to illustrate how peptide identification in mass spectra works
using database search engines like [MS Amanda](https://pubs.acs.org/doi/full/10.1021/pr500202e).

## Usage

**How the game works:**
- Read through the [game instructions](https://github.com/michabirklbauer/peptide_matching_game/blob/master/Game_Rules.pdf).

**Setting up the game:**
- Print the [game poster](https://github.com/michabirklbauer/peptide_matching_game/blob/master/Game_Poster.pdf).
- Print at least one copy of each spectrum in `spectrum_cards`.
- Print the [game instructions](https://github.com/michabirklbauer/peptide_matching_game/blob/master/Game_Rules.pdf) for people to understand the game.
- [Optional] Set up your own game solution browser or use [https://michabirklbauer.github.io/peptide_matching_game/](https://michabirklbauer.github.io/peptide_matching_game/) so people are able to check their solutions.

**Setting up the game solution browser:**
- Install requirements: `pip install -r requirements.txt`
- Run streamlit app: `streamlit run streamlit_app.py`
- Alternatively pull and run the docker container: `docker run -p 8501:8501 michabirklbauer/peptidematchinggame:latest`
- Open your browser and navigate to `localhost:8501`.

## References

- PDB structure [3RFM](https://www.rcsb.org/structure/3RFM) by [Dore et al.](http://dx.doi.org/10.1016/j.str.2011.06.014) is shown on the poster.

## License

- [MIT](https://github.com/michabirklbauer/peptide_matching_game/blob/master/LICENSE)

## Contact

- [[email protected]](mailto:[email protected])
92 changes: 92 additions & 0 deletions resources/createSpectra.py
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#!/usr/bin/env python3

from matplotlib import pyplot as plt
import ms2pip.single_prediction
import spectrum_utils.spectrum as spectrum
import spectrum_utils.plot as spectrum_plot

## 5 x 4 matrix

peptide_1 = "PLPGER"
peptide_2 = "FIYAYR"
peptide_3 = "GEQVSLR"
peptide_4 = "DRYIAIR"
peptide_5 = "ARSTLQK"

# a 3 - easy
# y4 matches only 3
peptides_1 = ["PLFGER", "PLHGER", "PLPGER", "PLGGER"]
# b 2 - medium
# b3 is only correct in 2
peptides_2 = ["FIFAYR", "FIYAYR", "FIHAYR", "FIKAYR"]
# c 3 - medium
# b3 intensity only matches 3
peptides_3 = ["GEQASLR", "GEQTSLR", "GEQVSLR", "GEQSSLR"]
# d 1 - hard
# b3 and y4 only correct in 1
peptides_4 = ["DRYIAIR", "DRYFAIR", "DRYWAIR", "DRYPAIR"]
# e 4 - hard
# b4 and b5 of 1, 2 are too intense, b4 of 3 is off by ~15 Da
peptides_5 = ["ARSILQK", "ARSLLQK", "ARSSLQK", "ARSTLQK"]

gridlines = False


all_peptides = [peptides_1,
peptides_2,
peptides_3,
peptides_4,
peptides_5]

def get_spectrum(peptide_sequence, charge = 1):

model = ms2pip.single_prediction.SinglePrediction()
mz, intensity, annotation = model.predict(peptide_sequence, "-", charge, model = "HCD2021")
identifier = f"{peptide_sequence}/{charge}/-"
precursor_mz = model.mod_info.calc_precursor_mz(peptide_sequence, "-", charge)
mod_dict = model._modifications_to_dict("-")
spectrum_annotation = model._get_sus_annotation(mz, annotation)

s = spectrum.MsmsSpectrum(identifier,
precursor_mz,
charge,
mz,
intensity,
annotation = spectrum_annotation,
peptide = peptide_sequence,
modifications = mod_dict)

return s

def main():
fig, axs = plt.subplots(5,4, figsize = (25,20), dpi = 300, tight_layout = True)
i = 0
rows = ["A", "B", "C", "D", "E"]
for peptide_group in all_peptides:
j = 0
for peptide in peptide_group:
s = get_spectrum(peptide)
spectrum_plot.spectrum(s, ax = axs[i, j])
axs[i, j].set_title(rows[i] + str(j + 1) + " - " + peptide)
axs[i, j].set_xlim([0, 900])
axs[i, j].grid(visible = gridlines, which = "both")
j += 1
i += 1

plt.savefig("result.svg")

def main2():
rows = ["A", "B", "C", "D", "E"]
for i, peptide in enumerate([peptide_1, peptide_2, peptide_3, peptide_4, peptide_5]):
s = get_spectrum(peptide)
fig = plt.figure(figsize = (8,4.5))
plt.title("Peptide Group " + rows[i])
spectrum_plot.spectrum(s)
plt.xlim([0, 900])
plt.grid(visible = gridlines, which = "both")
plt.savefig(rows[i] + ".svg")


if __name__ == "__main__":
main()
main2()
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