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Differential expression detection between gene expression time series experiments with confounder correction and timehift detection.

Project description

Package for using GPTwoSample

This module allows the user to compare two timelines with respect to
diffferential expression.

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 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 for further details.

Examples: Please see 'ready-to-use' example scripts in
./gptwosample/examples. (In your python site-packages folder, see for further details)

Example run: $ exdir=gptwosample/examples/ $ gptwosample -vtpo toy
$exdir/ToyCondition1.csv $exdir/ToyCondition2.csv

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" and then
run it by "./"

Make sure to run "python ./examples/" to
generate toy data for examples, if they are not present.

Project details

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gptwosample-0.1.19.tar.gz (1.8 MB view hashes)

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