Commit 4ae782fd authored by Mathias Walzer's avatar Mathias Walzer

updated readme and some todos, rm refactored file

parent 78230679
Pipeline #77901 passed with stages
in 4 minutes and 19 seconds
......@@ -372,7 +372,7 @@ def describeErrorRates(identification_accuracy_metrics:mzqc.QualityMetric) -> Li
return metrics
# TODO target decoy separation and FDR
# TODO target decoy separation and FDR, correct name would be getSamplingRates not ratios
def getSamplingRatios(identification_sequence_metrics:mzqc.QualityMetric) -> List[mzqc.QualityMetric]:
"""
getSamplingRatios calculates the sampling ratio metric for identified tandem spectra.
......
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# QCCalculator
Development for python driven QC calculation (QCCalculator) and presentation (QSpector)
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Development for python driven QC calculation (QCCalculator) and presentation (QSpector)
## Install
pip install -U git+https://github.com/bigbio/qccalculator.git#egg=QCCalculator
## Dependencies
- biopython
- click
- mzqc-pylib
- pandas
- plotly-express
- pronto
- pyopenms
- requests
- toposort
See setup.py for most recent listing.
## Development
Structure:
QCCalculator is structured as a click applications project.
The `cli.py` module contains the application code calling the metric calculation (from the other modules), data input (from pyopenms and pandas), and mzQC assembly (from mzqc-pylib).
The other modules contain metric calculation code for metric calculation and value collection split per topic of metrics.
### Contribution
For example, to add a new input from mzTab, you need a new module `mztab.py` to read the identification data. You also need to extend the command function for full QC in `cli.py`. The code should accept the results of `mztab.py`, optimally directly using the umbrella function `getIDQuality`. If that is not possible, you'd need to add a `idqcmztab.py` module to reuse the metric calculations with more direct input of values.
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