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A package for ranking differentially expressed gene expression time courses through Gaussian process regression. gprege fits two GPs with the an RBF (+ noise diagonal) kernel on each profile. One GP kernel is initialised wih a short lengthscale hyperparameter, signal variance as the observed variance and a zero noise variance. It is optimised via scaled conjugate gradients (netlab). A second GP has fixed hyperparameters: zero inverse-width, zero signal variance and noise variance as the observed variance. The log-ratio of marginal likelihoods of the two hypotheses acts as a score of differential expression for the profile. Comparison via ROC curves is performed against BATS.

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gprege classification

gprege specifications

Unique identifier:
OMICS_02011
Interface:
Command line interface
Operating system:
Unix/Linux, Mac OS, Windows
License:
GNU Affero General Public License version 3
Stability:
Stable
Software type:
Package/Module
Restrictions to use:
None
Programming languages:
R
Computer skills:
Advanced
Maintained:
Yes

gprege distribution

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No versioning.

gprege support

Documentation

Credits

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Publications

Institution(s)

The Sheffield Institute for Translational Neuroscience, Sheffield, UK

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