Manual for gmkin

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Starting gmkin

As gmkin is an R package, you need to start R and load the gmkin package before you can run gmkin. The latter can be achieved by entering the command

library(gmkin)

+library(gmkin)

into the R console. This will also load the packages that gmkin depends on, most notably gWidgetsWWW2 and mkin. Loading the package only has to be done once after you have started R.

Before you start gmkin, you should make sure that R is using the working directory that you would like to keep your gmkin project file(s) in. If you use the standard R GUI application on windows, you can change the working directory from the File menu (‘File’ -> ‘Change dir…’).

Once you are sure that the working directory is what you want it to be, gmkin can be started by entering the R command

gmkin()

+gmkin()

This will cause the default browser to start up or, if it is already running, to pop up and open a new tab for displaying the gmkin user interface.

In the R console, you should see a message that the httpd help server is started, if it wasn’t already started before.

In the browser, you should see something like the screenshot below.

Screenshot of the newly started gmkin GUI

The statusbar at the bottom of the gmkin window shows, among others, the working directory that gmkin uses.

If the browser only shows “Loading ExtJS…” and nothing else happens for about 10 to 15 seconds, please enter the gmkin() command again in the R console. If this still does not bring up the gmkin GUI, please close the browser and try again.

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A gmkin project workspace contains datasets, kinetic models for fitting, and so-called fits, i.e. the results of fitting models to data. The project area also shows the current working directory, where project workspace files are saved using the file extension .gmkinws.

Once a project has been saved by the user, the project explorer to the left will show it in the project list.

Screenshot of saving a new project

The current state of a project should repeatedly be saved during the work in order to avoid loosing data. This can be achieved by selecting the ‘Project’ tab in the center and pressing the ‘Save project to project file’ button. More conveniently, the keyboard shortcut Shift-F12 (was Ctrl-X in gmkin < 0.6.6) can be used to save the current status of the project.

In the project file management area, datasets and models can be imported from one of the projects in the project list, once it has been selected in the droplist labelled ‘Import from:’.

Screenshot of importing datasets and models

Once the project has been set up, you may want to minimize the project explorer, especially if you are limited in vertical screen space.

Screenshot of minimized project explorer

@@ -141,7 +150,7 @@ Dataset editor

When you select one of the datasets in the dataset explorer to the left, some summary information about the dataset is shown in the center, and the data itself is loaded into the data editor to the right.

Screenshot of the GUI after loading a dataset

When you have added information about the units, or edited the data to the right, you should hit the button ‘Keep changes’. This will add a new entry in the dataset explorer.

In the dataset editor to the right, you can override original data (for example in order to follow FOCUS recommendations for time zero samples or values below the limit of detection) by entering numbers in the override column.

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Entering data directly

For entering new data manually, there are two possibilities. You can either change the Dataset title of the current dataset and edit the data in the Data editor to the right. Or, if the new data should have a different structure, e.g. different sampling times, observed variables and replicates, click on “New dataset”, edit the dataset title, sampling times, number of replicates and the list of observed variables, and press the button ‘Generate grid for entering kinetic data’, in order to prepare the Data editor to the right.

For sampling times and short names of the relevant compounds, a comma separated list must be entered, with a space after each comma. An example of filling out the respective fields is shown below.

Screenshot of generating a data grid

After that, the actual measurements can be entered into the Data editor to the right, in the column ‘value’.

If everything is OK, press “Keep changes” to save the dataset in the current workspace. Note that you need to save the project file (see above) in order to be able to use the dataset that you created in a future gmkin session.

@@ -163,17 +172,18 @@ Importing data from text files

In case you want to work with a larger dataset that is already available as a computer file e.g. in a spreadsheet application, you can export these data as a tab separated or comma separated text file and import it using the “Browse” and “Upload” buttons in the dataset editor.

As an example, we can create a text file from one of the datasets shipped with the mkin package using the following R command:

write.table(schaefer07_complex_case, sep = ",", dec = ".",
-            row.names = FALSE, quote = FALSE,
-            file = "schaefer07.csv")

+write.table(schaefer07_complex_case, sep = ",", dec = ".",
+            row.names = FALSE, quote = FALSE,
+            file = "schaefer07.csv")

This produces a text file with comma separated values in the current working directory of R.

Loading this text file into gmkin using the “Browse” and “Upload” buttons

Screenshot of the browse and upload dialogue

results in an an import configuration area showing the top lines of the imported file, and giving the possibility to chose the import options matching the file format.

Screenshot of the import configuration area

In the import configuration area, the following options can be specified. In the field “Comment lines”, the number of lines in the beginning of the file that should be ignored can be specified.

The checkbox on the next line should be checked if the first line of the file contains the column names, i.e. the names of the observed variables when the data are in wide format.

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As the “Decimal” separator, comma “,” or period “.” can be selected.

In the next line, it can be specified if the data are in wide or in long format. If in wide format, the only option left to specify is the title of the column containing the sampling times. If the data is in long format, the column headings specifying the columns containing the observed variables (default is “name”), the sampling times (default is “time”), the observed values (default is “value”) and, if present in the data, the relative errors (default is “err”) can be adapted. The default settings appearing if the long format is selected are shown below.

Screenshot of the default variable names for data in long format

In our example we have data in the wide format, and after adapting the “Separator” to a comma, we can press the button “Import using options specified below”, and the data should be imported. If successful, the dataset editor should show the sampling times and the names of the observed variables, and the Data editor should show the imported data in a grid for further editing or specifying overrides.

Screenshot of a successful upload

After adapting the dataset title and possibly the units, press “Keep changes” to save the dataset in the current workspace. Again, you need to save the project file in order to be able to use the dataset that you created in a future gmkin session.

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The following screenshot shows the model editor for the model ‘Z.2a.ff’ from the project workspace ‘FOCUS_2006_Z’ provided with the gmkin package.

Screenshot of the model editor

In the first line the name of the model can be edited. You can also specify “min” or “max” for minimum or maximum use of formation fractions. Maximum use of formation fractions means that the differential equations in the degradation model are formulated using formation fractions. When you specify “min”, then formation fractions are only used for the parent compound when you use the FOMC, DFOP or the HS model for it.

Pressing “Add observed variable” adds a line in the array of state variable specifications below. The observed variables to be added are usually transformation products (usually termed metabolites), but can also be the parent compound in a different compartment (e.g. “parent_sediment”).

Only observed variable names that occur in previously defined datasets or models can be selected. For any observed variable other than the first one, only the SFO or the SFORB model can be selected. For each observed variables, a comma separated list of target variables can be specified. In addition, a pathway to the sink compartment can be selected. If too many observed variables have been added, complete lines can be removed from the model definition by pressing the button “Remove observed variable”.

If the model definition is supposedly correct, press “Keep changes” to make it possible to select it for fitting in the listing of models to the left.

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If a dataset and a kinetic model are selected, the button “Configure fit” below in the Explorer window “Configuration” becomes active. Pressing it opens the “Configuration” area in the center and loads the dataset into the Data editor to the right, for viewing only.

After pressing the button ‘Plot unoptimised’, the data and the kinetic model with default starting parameters are plotted in the ‘Plot’ area to the right.

Screenshot of the fit configuration area

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In the right part of the fit configuration area, the file format can be chosen, the legend can be turned off, and the observed variables for which the data and the model fit should be plotted can be selected as shown below.

plot options

On systems running the Windows operating system, the enhanced metafile (emf) format can be additionally chosen. Changing the file format for plotting will also change the extension of the proposed filename for saving the plot.

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Fitting the model

In many cases the starting parameters and the fit options do not need to be modified and the model fitting process can simply be started by pressing the “Run fit” button. In the R console, the progressive reduction in the model cost can be monitored and will be displayed in the following way:

> Ordinary least squares optimisation
-Sum of squared residuals at call 1: 2388.077
-Sum of squared residuals at call 3: 2388.077
-Sum of squared residuals at call 4: 247.1962
-Sum of squared residuals at call 7: 200.6791
-Sum of squared residuals at call 10: 197.7231
-Sum of squared residuals at call 11: 197.0872
-Sum of squared residuals at call 14: 196.535
-Sum of squared residuals at call 15: 196.535
-Sum of squared residuals at call 16: 196.535
-Sum of squared residuals at call 17: 196.5334
-Sum of squared residuals at call 20: 196.5334
-Sum of squared residuals at call 25: 196.5334
-Negative log-likelihood at call 31: 26.64668
-Optimisation successfully terminated.

> Ordinary least squares optimisation
+Sum of squared residuals at call 1: 2388.077
+Sum of squared residuals at call 3: 2388.077
+Sum of squared residuals at call 4: 247.1962
+Sum of squared residuals at call 7: 200.6791
+Sum of squared residuals at call 10: 197.7231
+Sum of squared residuals at call 11: 197.0872
+Sum of squared residuals at call 14: 196.535
+Sum of squared residuals at call 15: 196.535
+Sum of squared residuals at call 16: 196.535
+Sum of squared residuals at call 17: 196.5334
+Sum of squared residuals at call 20: 196.5334
+Sum of squared residuals at call 25: 196.5334
+Negative log-likelihood at call 31: 26.64668
+Optimisation successfully terminated.

If plotting of the fitting progress was selected, a new separate graphics window should either pop up, or a graphics window previously started for this purpose will be reused.

If your screen size allows for it, you can arrange the R plotting window and the R console in a way that you can see everything at the same time:

Screenshot of arrangement of plot window and console

Once a fit has successfully been completed, the most important results are shown in several tables in the “Result” area as shown below.

The complete summary can be saved into a text file by specifying a suitable file name and pressing the button “Save summary”.

Manual for gmkin

Johannes Ranke

2020-02-07

2021-02-12

Starting gmkin

Entering data directly

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Fitting the model

Confidence interval plots

-Contents