bioconda / packages / bioconductor-gprege 1.32.0

Gaussian Process Ranking and Estimation of Gene Expression time-series


Info: This package contains files in non-standard labels.

conda install

  • noarch  v1.32.0
To install this package with conda run one of the following:
conda install -c bioconda bioconductor-gprege
conda install -c bioconda/label/gcc7 bioconductor-gprege


The gprege package implements the methodology described in Kalaitzis & Lawrence (2011) "A simple approach to ranking differentially expressed gene expression time-courses through Gaussian process regression". The software 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 (Angelini, 2007). A detailed discussion of the ranking approach and dataset used can be found in the paper (

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