v1.0.0 release

.github/workflows/python-app.yml

@@ -0,0 +1,45 @@
+# This workflow will install Python dependencies, run tests and lint with a variety of Python versions
+# 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: msannika_fdr
+
+on:
+  push:
+    branches: [ master ]
+  pull_request:
+    branches: [ master ]
+
+jobs:
+  build:
+
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: ['3.7', '3.8', '3.9', '3.10', '3.11', '3.12']
+
+    steps:
+    - uses: actions/checkout@v3
+    - name: Set up Python ${{ matrix.python-version }}
+      uses: actions/setup-python@v3
+      with:
+        python-version: ${{ matrix.python-version }}
+    - name: Copy scripts and data to "/tests"
+      run: |
+        cp msannika_fdr.py tests
+        cp data/DSSO_Crosslinks.xlsx .
+        cp data/DSSO_CSMs.xlsx .
+    - name: Install dependencies
+      run: |
+        python -m pip install --upgrade pip
+        python -m 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
+    - name: Test with pytest
+      run: |
+        pytest tests/tests.py

README.md

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-# MSAnnika_FDR
+![workflow_state](https://github.com/hgb-bin-proteomics/MSAnnika_FDR/workflows/msannika_fdr/badge.svg)
+
+# MS Annika FDR
+
+A script and functions to group and validate [MS Annika](https://github.com/hgb-bin-proteomics/MSAnnika)
+results. The main use case would be for re-validating results after filtering or
+merging results from different MS Annika runs.
+
+## Usage
+
+- Install python 3.7+: [https://www.python.org/downloads/](https://www.python.org/downloads/)
+- Install requirements: `pip install -r requirements.txt`
+- Export MS Annika results from Proteome Discoverer to Microsoft Excel format.
+- Run `python msannika_fdr.py filename.xlsx -fdr 0.01` (see below for more examples).
+- The script may take a few minutes, depending on the number of CSMs/crosslinks to process.
+- Done!
+
+## Examples
+
+`msannika_fdr.py` takes one positional and one optional argument. The first
+argument always has to be the filename(s) of the MS Annika result file(s). You
+may specify any number of result files, keep in mind however that
+`msannika_fdr.py` will process these files seperately, if you want to merge
+several result files, check out [MS Annika Combine Results](https://github.com/hgb-bin-proteomics/MSAnnika_Combine_Results).
+For demonstration purposes we will use the files supplied in the `/data` folder:
+- `DSSO_Crosslinks.xlsx` contains unvalidated crosslinks from an MS Annika
+search.
+- `DSSO_CSMs.xlsx` contains unvalidated CSMs from an MS Annika search.
+
+The following is a valid `msannika_fdr.py` call:
+
+```bash
+python msannika_fdr.py DSSO_Crosslinks.xlsx
+```
+
+This will not do anything because no FDR was given. You should see in the output
+that the script skipped the file. However, doing the same with a CSM file
+results in a different output:
+
+```bash
+python msannika_fdr.py DSSO_CSMs.xlsx
+```
+
+This will group the CSMs by sequence and position to crosslinks and you should
+see a file `DSSO_CSMs_crosslinks.xlsx` generated.
+
+If you suppy the optional argument `-fdr` or `--false_discovery_rate` and the
+desired FDR as a floating point number, the results will be validated:
+
+```bash
+python msannika_fdr.py DSSO_Crosslinks.xlsx -fdr 0.01
+```
+
+This will validate the input crosslinks for estimated 1% FDR and will generate a
+a file called `DSSO_Crosslinks_validated.xlsx` containing only crosslinks above
+the estimated 1% FDR threshold. Note that the following command will produce the
+same output (FDR values >= 1 will automatically be divided by 100):
+
+```bash
+python msannika_fdr.py DSSO_Crosslinks.xlsx -fdr 1
+```
+
+Validating a CSMs file works the same way:
+
+```bash
+python msannika_fdr.py DSSO_CSMs.xlsx -fdr 0.01
+```
+
+This will will validate the input CSMs for estimated 1% FDR and will generate a
+a file `DSSO_CSMs_validated.xlsx` containing only CSMs above the estimated 1%
+FDR threshold. Furthermore, it will group the input CSMs to crosslinks and
+output them to the file `DSSO_CSMs_crosslinks.xlsx` and then validate those
+crosslinks for 1% estimated FDR and store the result in
+`DSSO_CSMs_crosslinks_validated.xlsx`.
+
+You can also supply several files to the script like this:
+
+```bash
+python msannika_fdr.py DSSO_CSMs.xlsx DSSO_Crosslinks.xlsx -fdr 0.01
+```
+
+This will process the input files seperately and sequentially and produce the
+files as mentioned above:
+- `DSSO_Crosslinks_validated.xlsx`
+- `DSSO_CSMs_validated.xlsx`
+- `DSSO_CSMs_crosslinks.xlsx`
+- `DSSO_CSMs_crosslinks_validated.xlsx`
+
+## Parameters
+
+```python
+"""
+DESCRIPTION:
+A script to group and validate results from MS Annika searches.
+USAGE:
+msannika_fdr.py f [f ...]
+                  [-fdr FDR][--false_discovery_rate FDR]
+                  [-h][--help]
+                  [--version]
+positional arguments:
+  f                     MS Annika result files in Microsoft Excel format (.xlsx)
+                        to process.
+optional arguments:
+  -fdr FDR, --false_discovery_rate FDR
+                        False discovery rate to validate results for. Supports
+                        both percentage input (e.g. 1) or fraction input (e.g.
+                        0.01). By default not set and the input results will
+                        just be grouped to crosslinks (if CSMs as input) or
+                        nothing will be done (if crosslinks as input).
+                        Default: None
+  -h, --help            show this help message and exit
+  --version             show program's version number and exit
+"""
+```
+
+## Function Documentation
+
+If you want to integrate the MS Annika FDR calculation into your own scripts,
+you can import the following functions as given:
+
+```python
+import pandas as pd
+
+crosslinks = pd.read_excel("DSSO_Crosslinks.xlsx")
+csms = pd.read_excel("DSSO_CSMs.xlsx")
+
+# Grouping CSMs to crosslinks
+from msannika_fdr import MSAnnika_CSM_Grouper
+Crosslinks_grouped_from_CSMs = MSAnnika_CSM_Grouper.group(csms)
+
+# The function signature of MSAnnika_CSM_Grouper.group is:
+def group(data: pd.DataFrame) -> pd.DataFrame:
+    """code omitted"""
+    return
+
+# Validating CSMs for 0.01 FDR
+from msannika_fdr import MSAnnika_CSM_Validator
+Validated_CSMs = MSAnnika_CSM_Validator.validate(csms, 0.01)
+
+# The function signature of MSAnnika_CSM_Validator.validate is:
+def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame:
+    """code omitted"""
+    return
+
+# Validating Crosslinks for 0.01 FDR
+from msannika_fdr import MSAnnika_Crosslink_Validator
+Validated_Crosslinks = MSAnnika_Crosslink_Validator.validate(crosslinks, 0.01)
+
+# The function signature of MSAnnika_Crosslink_Validator.validate is:
+def validate(data: pd.DataFrame, fdr: float) -> pd.DataFrame:
+    """code omitted"""
+    return
+```
+
+## Known Issues
+
+[List of known issues](https://github.com/hgb-bin-proteomics/MSAnnika_FDR/issues)
+
+## Citing
+
+If you are using the MS Annika FDR script please cite:
+```
+MS Annika 2.0 Identifies Cross-Linked Peptides in MS2–MS3-Based Workflows at High Sensitivity and Specificity
+Micha J. Birklbauer, Manuel Matzinger, Fränze Müller, Karl Mechtler, and Viktoria Dorfer
+Journal of Proteome Research 2023 22 (9), 3009-3021
+DOI: 10.1021/acs.jproteome.3c00325
+```
+
+If you are using MS Annika please cite:
+```
+MS Annika 2.0 Identifies Cross-Linked Peptides in MS2–MS3-Based Workflows at High Sensitivity and Specificity
+Micha J. Birklbauer, Manuel Matzinger, Fränze Müller, Karl Mechtler, and Viktoria Dorfer
+Journal of Proteome Research 2023 22 (9), 3009-3021
+DOI: 10.1021/acs.jproteome.3c00325
+```
+or
+```
+MS Annika: A New Cross-Linking Search Engine
+Georg J. Pirklbauer, Christian E. Stieger, Manuel Matzinger, Stephan Winkler, Karl Mechtler, and Viktoria Dorfer
+Journal of Proteome Research 2021 20 (5), 2560-2569
+DOI: 10.1021/acs.jproteome.0c01000
+```
+
+## License
+
+- [MIT](https://github.com/hgb-bin-proteomics/MSAnnika_FDR/blob/master/LICENSE)
+
+## Contact
+
+- [micha.birklbauer@fh-hagenberg.at](mailto:micha.birklbauer@fh-hagenberg.at)