Optimus: a general purpose adaptive optimisation engine in R

Abstract

MotivationMany calculations in computational biology necessitate a use of a probabilistic optimisation protocol to determine a set of parameters that capture the system at a desired state in the configurational space. Here, we developed a flexible optimisation engine in R that can be plugged to any, simple or complex, modelling initiative through a few lucid interfacing functions, to perform a seamless optimisation with rigorous parameter sampling. ResultsOptimus features an acceptance ratio simulated annealing, acceptance ratio replica exchange, and adaptive thermoregulation, thus driving a Monte Carlo optimisation process in a flexible manner, through constrained acceptance frequency but unconstrained adaptive pseudo temperature regiments. We show the applicability of our R optimiser to a wide variety of problems spanning data analyses and computational biology tasks. Availability and ImplementationOptimus is written and implemented in R, and is freely available from the http://github.com/SahakyanLab/Optimus repository. Contactaleksandr.sahakyan@imm.ox.ac.uk Supplementary InformationSupplementary information with more details, tutorials, and developer instructions is available. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=72 SRC="FIGDIR/small/476810v1_ufig1.gif" ALT="Figure 1"> View larger version (10K): org.highwire.dtl.DTLVardef@749b4aorg.highwire.dtl.DTLVardef@17f439eorg.highwire.dtl.DTLVardef@303ad6org.highwire.dtl.DTLVardef@66dda7_HPS_FORMAT_FIGEXP M_FIG The Optimus software logo depicting two gears ("Op") that drag the system "s", trapped in a "u" minimum, through a rough solution landscape into a more favourable solution with a deeper pseudo-energy minimum ("p"). C_FIG