kfwx 1.0.0

A data analysis toolkit for the KFW lab (MacOS X)

KFWX Data Analysis Toolkit

This is a toolkit for MacOS X and Windows that automatically analyzes data for assays.

1. Installing KFWX
   • For MacOS X
   • For Windows
2. Tools Available
3. Using the Data Analysis Tools (Tools 1-3)
4. Using the Merge Tools (Tools 4-6)
5. Understanding the Output

Installing KFWX on MacOS X

1. Ensure that Python 2.7 is installed. Python 2.7 should already be installed with MacOS X.
   • Open your Terminal and run the command python --version.
   • If the response is Python 2.7.XX then you have the correct version of Python installed. Otherwise, you should follow the installation instructions at https://docs.python-guide.org/starting/install/osx/#install-osx.
2. Make sure that pip is installed.
   • Run the command pip --version.
   • If the response is pip XX.X from ... (python 2.7) then you have the correct version of pip installed. Otherwise, you should follow the installation instructions at https://ehmatthes.github.io/pcc/chapter_12/installing_pip.html#pip-on-os-x.
3. Install kfwx from the Python Package Index with pip.
   • Type the command pip install --upgrade kfwx.
4. You must have also some other Python modules installed.
   • matplotlib
   • pandas
   • seaborn
   • xlrd
   • openpyxl Use the command pip install matplolib pandas seaborn xlrd openpyxl. This may take a few minutes to finish.

Installing KFWX on Windows

1. Ensure that Python 2.7 is installed (preferably the latest version).
   • Open your Command prompt and run the command python --version.
   • If the response is Python 2.7.XX then you have the correct version of Python installed. Otherwise, you should download the latest Python 2.7 Windows installer, open the installer, and follow the installation instructions (Python 2.7.15 is the latest at this time) https://www.python.org/downloads/release/python-2715/.
   • NOTE: If you think Python is installed but the above command does not work, try the command C:\Python27\python.exe --version. If this command works but not the above command, then consider following these instructions to add python to your PATH environment variables.
     1. Open the Advanced System Settings.
     2. Click Environment Variables.
     3. Select New.
     4. Enter python as the Variable Name and C:\Python27 as the Variable Value.
     5. Restart your Command prompt.
   • If you choose not to do this, then you must replace python with C:\Python27\python.exe from here on out.
2. Make sure that pip is installed. If you have the latest version of Python 2.7, then pip should already be installed.
   • Run the command pip --version.
   • If the response is pip XX.X from ... (python 2.7) then you have the correct version of pip installed. Otherwise, you should follow the installation instructions at https://ehmatthes.github.io/pcc/chapter_12/installing_pip.html#pip-on-os-x.
   • NOTE: If you think pip is installed but the above command does not work, try the command C:\Python27\Scripts\pip.exe --version. If this command works but not the above command, then consider following these instructions to add pip to your PATH environment variables.
     1. Open the Advanced System Settings.
     2. Click Environment Variables.
     3. Double click the Path variable.
     4. Select New.
     5. Enter C:\Python27\Scripts.
     6. Restart your Command prompt.
   • If you choose not to do this, then you must replace pip with C:\Python27\Scripts\pip.exe from here on out.
3. Install kfwy from the Python Package Index with pip.
   • Type the command pip install --upgrade kfwx.
4. You must have also some other Python modules installed.
   • matplotlib
   • pandas
   • seaborn
   • xlrd
   • openpyxl Use the command pip install matplolib pandas seaborn xlrd openpyxl. This may take a few minutes to finish.

Tools Available

1. Membrane Potential
2. NADH Redox
3. H2O2
4. Membrane Potential Merge
5. NADH Redox Merge
6. H2O2 Merge

Using the Data Analysis Tools (Tools 1-3)

1. Place the raw data files (.txt) to be analyzed in a folder.
2. Open the command line (terminal for Mac and command prompt for Windows)
3. Navigate to the folder
   • e.g. if folder path is users/data_analysis, then type the command cd users/data_analysis
   • NOTE: If you are having difficulty figuring out what your folder path is, then open a window for your command line and drag your folder into the window. It will show you the file path.
4. Type command python -m kfwx to run the toolkit and then follow the instructions provided

Using the Merge Tools (Tools 4-6)

1. Place the excel files (.xlsx) to be merged in a folder.
2. Open the command line
3. Navigate to the folder
   • e.g. if folder path is users/data_analysis, then type the command cd users/data_analysis
4. Type command python -m kfwx to run the toolkit and then follow the instructions provided

Understanding the Output

This section explains in detail the significance of the results of the data analysis.

Membrane Potential

1. Metadata Sheet - This sheet hosts information about the experiment itself
   • ID - The experimental ID.
   • Standard Curve - A true or false value indicating whether or not the standard curve calculation was used.
   • Slope - The slope value entered by the researcher to be used in calculations.
   • Y-Intercept - The y-intercept value entered by the researcher to be used in calculations.
   • Substrates - A column containing the list of substrates used in the experiment.
   • Additions - A column containing the list of additions used in the experiment.
   • Date - The date the analysis was run in the form YYYY-MM-DD.
2. Raw Data - The raw data taken from the lab tools.
   • The data is in the form X | Y | X |...
3. Averaged Raw Data - The average membrane potential for 3-minute (i.e., 180 seconds) increments in each data set. Each data set is annotated with the buffer conditions of the assay at that time.
4. Corrected Raw Data - The same data as the Average Raw Data sheet, but with an additional correction calculation which divides each average membrane potential by the the average membrane potential for Ala.
5. Standard Curve Data - The results of the standard curve calculation on the raw data.
   • The data is in the form X | Y | X |...
6. Averaged Standard Curve - The results of the standard curve calculation on the averaged data.

NADH Redox

1. Metadata Sheet - This sheet hosts information about the experiment itself.
   • ID - The experimental ID.
   • Substrates - A column containing the list of substrates used in the experiment.
   • Additions - A column containing the list of additions used in the experiment.
   • Date - The date the analysis was run in the form YYYY-MM-DD.
2. Raw Data - The raw data taken from the lab tools.
   • The data is in the form X | Y | X |...
3. Stripped Data - Contains only the columns that correspond to the NADH data points.
   • The data is in the form X | Y | X |...
4. Reduced Data - The same data as the Stripped Data sheet, but with an additional reduction calculation.
   • y_new = (y_old-min)/(max-min)*100
5. Averaged Reduced Data - The averages of the reduced data for 3-minute (i.e., 180 seconds) increments in each data set. Each data set is annotated with the buffer conditions of the assay at that time.

H2O2

1. Metadata Sheet - This sheet hosts information about the experiment itself
   • ID - The experimental ID.
   • Standard Curve - A true or false value indicating whether or not the standard curve calculation was used.
   • Slope - The slope value entered by the researcher to be used in calculations.
   • Y-Intercept - The y-intercept value entered by the researcher to be used in calculations.
   • Substrates - A column containing the list of substrates used in the experiment.
   • Additions - A column containing the list of additions used in the experiment.
   • Mitochondria - The amount of mitochondria use (in milligrams).
   • Date - The date the analysis was run in the form YYYY-MM-DD.
2. Raw Data - The raw data taken from the lab tools.
   • The data is in the form X | Y | X |...
3. Slopes Data - The slope for 3-minute (i.e., 180 seconds) increments in each data set. Each data set is annotated with the buffer conditions of the assay at that time.
4. Corrected Slopes - The same data as the Slopes sheet, but with an additional correction calculation which divides each slope value by the mg of mitochondria used.
5. Standard Curve - The results of the standard curve calculation on the Raw Data.
6. Standard Curve Slopes - The results of the standard curve calculation on the Slopes Data.
7. Corrected Standard Curve Slopes - The results of the correction calculation on the Standard Curve Slopes data.

Membrane Potential Merge

Combines data from all of the Averaged Standard Curve sheets in the Membrane Potential data analysis Excel files. Each row corresponds to a substrate. The Mean and SEM is calculated for each row.

NADH Redox Merge

Combines data from all of the Averaged Reduced Data sheets in the NADH Redox data analysis Excel files. Each row corresponds to a substrate. The Mean and SEM is calculated for each row.

H2O2 Merge

Combines data from all of the Corrected Standard Curve Slopes sheets in the H2O2 data analysis Excel files. Each row corresponds to a substrate. The Mean and SEM is calculated for each row.