updated readme and some todos, rm refactored file

QCCalculator/idqc.py

@@ -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.

README.md

 # QCCalculator
 
-Development for python driven QC calculation (QCCalculator) and presentation (QSpector)
\ No newline at end of file
+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.  
\ No newline at end of file