Differential expression detection between gene expression time series experiments with confounder correction and timehift detection.
This module allows the user to compare two timelines with respect to
It compares two timeseries against each other, depicting whether these
two timeseries were more likely drawn from the same function, or from
different ones. This prediction is defined by which covariance
function :py:class:`pygp.covar` you use.
To use gptwosample without installing: $ python gptwosample --help
To install gptwosample run: $ easy_install gptwosample or run:: $
python setup.py install from gptwosample directory if you downloaded
the source. This will install a script gptwosample into your python
bin. In some cases this bin is not in $PATH and must be included
Try printing the full help of the script using:: gptwosample --help
restart your unix shell if it is not yet registered.
To run optional package tests before installing run: python setup test
After installation you can use GPTwoSample with all it's features.
See doc/index.html for the documentation in your site-packages folder,
see www.python.org for further details.
Examples: Please see 'ready-to-use' example scripts in
./gptwosample/examples. (In your python site-packages folder, see
www.python.org for further details)
Example run: $ exdir=gptwosample/examples/ $ gptwosample -vtpo toy
To see for example GPTimeShift example, run
The Output will be saved in gptimeshift_example/ with plots and
results.csv. If you don't have sh, you can still run the script by
modifying the scripts via "chmod -x gptimeshift_example.sh" and then
run it by "./gptimeshift_example.sh"
Make sure to run "python ./examples/generateToyExampleFiles.py" to
generate toy data for examples, if they are not present.
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
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