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 et.al, 2007). A detailed discussion of the ranking approach and dataset used can be found in the paper (http://www.biomedcentral.com/1471-2105/12/180).
Package details |
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Author | Alfredo Kalaitzis <alkalait@gmail.com> |
Bioconductor views | Bioinformatics DifferentialExpression Microarray Preprocessing TimeCourse |
Maintainer | Alfredo Kalaitzis <alkalait@gmail.com> |
License | AGPL-3 |
Version | 1.34.0 |
URL | |
Package repository | View on Bioconductor |
Installation |
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