made explicit the need to edit the options file in the README

Author: stavis1

README.md

@@ -1,29 +1,32 @@
 
+
 # LipoCLEAN: A machine learning based quality filter for lipid identifications from MS-DIAL
 There are three ways to install and run LipoCLEAN: as an executable, as a docker container, and as a python package.
 
 ## The executable version
 This method requires no installation but it is somewhat slower than the other options.
 1. Download the executable for your operating system, the trained model, and the example options file from the [releases page](https://github.com/stavis1/lipoCLEAN/releases).
 2. Extract `example_analysis.zip` and `QE_Pro_model.zip` into the same folder. There should be no folders nested under `QE_Pro_model/` and all files from `example_analysis.zip` should be in the top level folder.
-3. Run `lipoCLEAN.exe --options example_analysis_options.txt`
+3. Run `lipoCLEAN.exe --options example_analysis_options.txt`.
 4. The results will be in a folder named `example_output/` the `example_output/QC/` folder contains several plots to assess the quality of the results.
-5. If you want a default version of the options file run `lipoCLEAN.exe --print options.txt`
+5. If you want a default version of the options file run `lipoCLEAN.exe --print options.txt`.
+6. To use the tool on other data edit the `options.txt` file.
 
 On some systems the warning `No module named 'brainpy._c.composition'` will be displayed. This is not an error and does not impact the running of the tool.
 
-## The conda version
-To set up the conda environment for the tool:
+## The Conda version
+To set up the Conda environment for the tool:
 1. Download the LipoCLEAN repository and navigate to the `environments` directory.
 2. Run `conda env create -p lipo_env --file lipoCLEAN.yml`
 3. Run `conda activate ./lipo_env`
 4. Navigate to the repository root.
 5. Run `pip install .`
-7. Download the trained model, and the example options file from the [releases page](https://github.com/stavis1/lipoCLEAN/releases).
-8. Extract `example_analysis.zip` and `QE_Pro_model.zip` into the same folder. There should be no folders nested under `QE_Pro_model/` and all files from `example_analysis.zip` should be in the top level folder.
-9. Run `python -m lipoCLEAN --options example_analysis_options.txt`
-10. The results will be in a folder named `example_output/` the `example_output/QC/` folder contains several plots to assess the quality of the results.
-11. If you want a default version of the options file run `python -m lipoCLEAN --print options.txt`
+6. Download the trained model, and the example options file from the [releases page](https://github.com/stavis1/lipoCLEAN/releases).
+7. Extract `example_analysis.zip` and `QE_Pro_model.zip` into the same folder. There should be no folders nested under `QE_Pro_model/` and all files from `example_analysis.zip` should be in the top level folder.
+8. Run `python -m lipoCLEAN --options example_analysis_options.txt`
+9. The results will be in a folder named `example_output/` the `example_output/QC/` folder contains several plots to assess the quality of the results.
+10. If you want a default version of the options file run `python -m lipoCLEAN --print options.txt`
+11. To use the tool on other data edit the `options.txt` file.
 
 On some systems the warning `No module named 'brainpy._c.composition'` will be displayed. This is not an error and does not impact the running of the tool.
 
@@ -34,6 +37,7 @@ The docker container has trained models provided under /models/. To use these ge
 3. Extract `QE_Pro_model.zip`.
 4. Run `docker run --rm -v /path/to/your/data/:/data/ stavisvols/lipoclean python -m lipoCLEAN --options /data/docker_example_analysis_options.txt`
 5. If you want the default docker options file run `docker run --rm -v /path/to/your/data/:/data/ stavisvols/lipoclean python -m lipoCLEAN --print /data/options.txt`
+6. To use the tool on other data edit the `options.txt` file.
 
 ## MS-Dial export settings for inference
 1. Click "Export" along the top bar
@@ -45,7 +49,7 @@ The docker container has trained models provided under /models/. To use these ge
 7. "Export format" should be "msp"
 8. Click Export
 
-A .txt will now be generated in the chosen directory with the information required for MSDpostprocess. The file name will start with "Mz"
+A .txt will now be generated in the chosen directory with the information required for LipoCLEAN. The file name will start with "Mz"
 
 ## Prepare training data
 1. Start with MS-DIAL exports using the same settings as described above for inference. 
@@ -65,3 +69,4 @@ The tool is capable of being trained on multiple input files. The retention time
 Our tests have shown that a model will likely generalize to a family of instruments but that this has limits. We expect that the QE_Pro_model will work for all orbitrap systems. We do not have the data necessary to know how well the TOF model will generalize to all TOF instruments so if you are working with e.g. TimsTOF data it would be a good idea to do an initial validation of the output. The publicly available datasets used were reprocessed from raw files and annotated in-house.
 
 Disclaimer: We are not in any way associated with the developers of MS-DIAL, we are merely enthusiastic users of their software.
+