Step by step tutorial & examples

Once the data has been prepared, gptwosample can be executed from the unix command line. See the full usage information in Parameter options.

See format for input data .csv files in Data format.

Make sure you either install gptwosample (Installing the package) .. or cd

into the extracted gptwosample folder before running this tutorial.

Try printing the full help of the script using:

python gptwosample --help

If an error occurs, you probably cd one level too deep and you can cd .. up one level.

In this tutorial we will build up a full usage call of gptwosample. First, we want to run gptwosample verbosly, thus the call so far looks like:

gptwosample -v

To enable plotting we provide the switch -p to the script:

gptwosample -v -p

We want to correct for timeshifts (more on Timeshift detection between replicates), thus we enable the timeshift switch -t:

gptwosample -v -p -t

Next we could additionally learn x confounding factors (see Accounting for confounding factors for details on confounding factors) and account for them while two-sampling:

gptwosample -v -p -t -c x

but we do not want to account for confounders in this tutorial.

The output of the script shall be in the subfolder ./tutorial/, so we add the output flag -o ./tutorial/:

gptwosample -v -p -t -o ./tutorial/

The script shall be run on the two toy condition files ToyCondition{1,2}.csv given in examples/ToyCondition{1,2}.csv. These files are non optional as this package is only for comparing two timeseries experiments to each other:

gptwosample -v -p -t -o ./tutorial/ examples/ToyCondition1.csv examples/ToyCondition2.csv

Note that the optional parameters could be collected together to give rise to a more compact call signature:

gptwosample -vpto tutorial examples/ToyCondition1.csv
examples/ToyCondition2.csv

After hitting return the script runs gptwosample on every gene given in the ToyCondition files and plots each gene into tutorial/plots/. One example plot will look like:

_images/timeshiftexample.pdf

The results are saved in the results.csv, which contains all predicted Bayes Factors and learnt covariance function parameters for all genes (Result structure).

For more tutorials and example files on how to use this package see gptwosample/examples.

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Package for using GPTwoSample